{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "0049dc55",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "os.environ[\"CUDA_VISIBLE_DEVICES\"] = \"1\"\n",
    "os.environ[\"HF_DATASETS_CACHE\"] = \"/mnt/data-ssd-1/data/huggingface-datasets\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "37718f6a",
   "metadata": {},
   "outputs": [],
   "source": [
    "import json\n",
    "with open(\"/home/georg/.secrets/secrets.json\") as f:\n",
    "    hf_auth_token = json.load(f)[\"anonymous_huggingface_access_token\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "1ae8759e",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[NeMo W 2022-09-24 12:58:28 optimizers:77] Could not import distributed_fused_adam optimizer from Apex\n"
     ]
    }
   ],
   "source": [
    "import time\n",
    "import os\n",
    "import tqdm\n",
    "import funcy\n",
    "import shutil\n",
    "import random\n",
    "import uuid\n",
    "import funcy\n",
    "import json\n",
    "import uuid\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import re\n",
    "\n",
    "from datasets import load_dataset\n",
    "\n",
    "from suno_utils.audio import Audio, Tokens\n",
    "from suno_utils.utils.metrics import get_wer\n",
    "from suno_utils.web.harvest import get_filename\n",
    "from suno_utils.utils.text import normalize_whitespace\n",
    "\n",
    "DATA_BASE_DIR = \"/mnt/data-ssd-1/data/academia/hf_paper\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "79e44dca",
   "metadata": {},
   "source": [
    "## Download all datasets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 348,
   "id": "7fcb06fe",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Reusing dataset ami (/mnt/data-ssd-1/data/huggingface-datasets/edinburghcstr___ami/ihm/0.0.0/537aefe880b1bc751994192a07baf57b4194785f9d79fc22c1c164eaf7c0370c)\n"
     ]
    }
   ],
   "source": [
    "ami_dev = load_dataset(\"edinburghcstr/ami\", \"ihm\", split=\"validation\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "38093a7d",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Reusing dataset tedlium (/mnt/data-ssd-1/data/huggingface-datasets/LIUM___tedlium/release3/1.0.1/3534cf671f9fe252aa91994765f9fbe95f9a077a67d56255dcd6645776ab997d)\n"
     ]
    }
   ],
   "source": [
    "ted_dev = load_dataset(\"LIUM/tedlium\", \"release3\", split=\"validation\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "8296975f",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Reusing dataset voxpopuli (/mnt/data-ssd-1/data/huggingface-datasets/polinaeterna___voxpopuli/en/1.3.0/8b39f6ff8dd8ced6def21f53eb18fbfd9701047d67b6c9da17f47f36ebedb4f8)\n"
     ]
    }
   ],
   "source": [
    "vox_dev = load_dataset(\"polinaeterna/voxpopuli\", \"en\", split=\"validation\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 303,
   "id": "69586fdf",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Reusing dataset spgispeech (/mnt/data-ssd-1/data/huggingface-datasets/kensho___spgispeech/dev/1.0.0/5fbf75dd9ef795a9b5a673457d2cbaf0b8fa0de8fb62acbd1da338d83a41e2f0)\n"
     ]
    }
   ],
   "source": [
    "spgi_dev = load_dataset(\"kensho/spgispeech\", \"dev\", split=\"validation\", use_auth_token=hf_auth_token)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 330,
   "id": "d903b267",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Reusing dataset gigaspeech (/mnt/data-ssd-1/data/huggingface-datasets/speechcolab___gigaspeech/dev/0.0.0/0db31224ad43470c71b459deb2f2b40956b3a4edfde5fb313aaec69ec7b50d3c)\n"
     ]
    }
   ],
   "source": [
    "giga_dev = load_dataset(\"speechcolab/gigaspeech\", \"dev\", split=\"validation\", use_auth_token=hf_auth_token)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 244,
   "id": "8f088275",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using custom data configuration sanchit-gandhi--earnings22_validation-290d6c2323ff83d9\n",
      "Reusing dataset parquet (/mnt/data-ssd-1/data/huggingface-datasets/sanchit-gandhi___parquet/sanchit-gandhi--earnings22_validation-290d6c2323ff83d9/0.0.0/2a3b91fbd88a2c90d1dbbb32b460cf621d31bd5b05b934492fdef7d8d6f236ec)\n"
     ]
    }
   ],
   "source": [
    "earnings22_dev = load_dataset(\"sanchit-gandhi/earnings22_validation\", \"validation\", split=\"validation\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 326,
   "id": "479cc912",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Reusing dataset common_voice_9_0 (/mnt/data-ssd-1/data/huggingface-datasets/mozilla-foundation___common_voice_9_0/en/9.0.0/c8491634a4579fef5745ab949ee9aa4265b7203d7e2ecf44f45879a6419cd40d)\n"
     ]
    }
   ],
   "source": [
    "cv9_dev = load_dataset(\n",
    "    \"mozilla-foundation/common_voice_9_0\", \"en\", split=\"validation\", use_auth_token=hf_auth_token\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "db515e95",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Reusing dataset librispeech_asr (/mnt/data-ssd-1/data/huggingface-datasets/librispeech_asr/all/2.1.0/14c8bffddb861b4b3a4fcdff648a56980dbb808f3fc56f5a3d56b18ee88458eb)\n",
      "Reusing dataset librispeech_asr (/mnt/data-ssd-1/data/huggingface-datasets/librispeech_asr/all/2.1.0/14c8bffddb861b4b3a4fcdff648a56980dbb808f3fc56f5a3d56b18ee88458eb)\n"
     ]
    }
   ],
   "source": [
    "libri_clean_dev = load_dataset(\"librispeech_asr\", \"all\", split=\"validation.clean\")\n",
    "libri_other_dev = load_dataset(\"librispeech_asr\", \"all\", split=\"validation.other\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "88cdaf6b",
   "metadata": {},
   "source": [
    "## Collect metadatas and audio"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "d2d51ed0",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Reusing dataset ami (/mnt/data-ssd-1/data/huggingface-datasets/edinburghcstr___ami/ihm/0.0.0/537aefe880b1bc751994192a07baf57b4194785f9d79fc22c1c164eaf7c0370c)\n",
      "Reusing dataset tedlium (/mnt/data-ssd-1/data/huggingface-datasets/LIUM___tedlium/release3/1.0.1/3534cf671f9fe252aa91994765f9fbe95f9a077a67d56255dcd6645776ab997d)\n",
      "Reusing dataset voxpopuli (/mnt/data-ssd-1/data/huggingface-datasets/polinaeterna___voxpopuli/en/1.3.0/8b39f6ff8dd8ced6def21f53eb18fbfd9701047d67b6c9da17f47f36ebedb4f8)\n",
      "Reusing dataset spgispeech (/mnt/data-ssd-1/data/huggingface-datasets/kensho___spgispeech/dev/1.0.0/5fbf75dd9ef795a9b5a673457d2cbaf0b8fa0de8fb62acbd1da338d83a41e2f0)\n",
      "Reusing dataset gigaspeech (/mnt/data-ssd-1/data/huggingface-datasets/speechcolab___gigaspeech/dev/0.0.0/0db31224ad43470c71b459deb2f2b40956b3a4edfde5fb313aaec69ec7b50d3c)\n",
      "Reusing dataset earnings22 (/mnt/data-ssd-1/data/huggingface-datasets/sanchit-gandhi___earnings22/validation/1.0.0/a90300100e71df30558766a136004e7803190bd4a6439991257a1bb74d986d25)\n",
      "Reusing dataset common_voice_9_0 (/mnt/data-ssd-1/data/huggingface-datasets/mozilla-foundation___common_voice_9_0/en/9.0.0/c8491634a4579fef5745ab949ee9aa4265b7203d7e2ecf44f45879a6419cd40d)\n",
      "Reusing dataset librispeech_asr (/mnt/data-ssd-1/data/huggingface-datasets/librispeech_asr/all/2.1.0/14c8bffddb861b4b3a4fcdff648a56980dbb808f3fc56f5a3d56b18ee88458eb)\n",
      "Reusing dataset librispeech_asr (/mnt/data-ssd-1/data/huggingface-datasets/librispeech_asr/all/2.1.0/14c8bffddb861b4b3a4fcdff648a56980dbb808f3fc56f5a3d56b18ee88458eb)\n"
     ]
    }
   ],
   "source": [
    "ami_dev = load_dataset(\"edinburghcstr/ami\", \"ihm\", split=\"validation\")\n",
    "ted_dev = load_dataset(\"LIUM/tedlium\", \"release3\", split=\"validation\")\n",
    "vox_dev = load_dataset(\"polinaeterna/voxpopuli\", \"en\", split=\"validation\")\n",
    "spgi_dev = load_dataset(\"kensho/spgispeech\", \"dev\", split=\"validation\", use_auth_token=hf_auth_token)\n",
    "giga_dev = load_dataset(\"speechcolab/gigaspeech\", \"dev\", split=\"validation\", use_auth_token=hf_auth_token)\n",
    "earnings22_dev = load_dataset(\"sanchit-gandhi/earnings22_validation\", \"validation\", split=\"validation\")\n",
    "cv9_dev = load_dataset(\n",
    "    \"mozilla-foundation/common_voice_9_0\", \"en\", split=\"validation\", use_auth_token=hf_auth_token\n",
    ")\n",
    "libri_clean_dev = load_dataset(\"librispeech_asr\", \"all\", split=\"validation.clean\")\n",
    "libri_other_dev = load_dataset(\"librispeech_asr\", \"all\", split=\"validation.other\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3219cbb9",
   "metadata": {},
   "outputs": [],
   "source": [
    "ami_dev = load_dataset(\"edinburghcstr/ami\", \"ihm\", split=\"validation\")\n",
    "ted_dev = load_dataset(\"LIUM/tedlium\", \"release3\", split=\"validation\")\n",
    "vox_dev = load_dataset(\"polinaeterna/voxpopuli\", \"en\", split=\"validation\")\n",
    "spgi_dev = load_dataset(\"kensho/spgispeech\", \"dev\", split=\"validation\", use_auth_token=hf_auth_token)\n",
    "giga_dev = load_dataset(\"speechcolab/gigaspeech\", \"dev\", split=\"validation\", use_auth_token=hf_auth_token)\n",
    "earnings22_dev = load_dataset(\"sanchit-gandhi/earnings22_validation\", \"validation\", split=\"validation\")\n",
    "cv9_dev = load_dataset(\n",
    "    \"mozilla-foundation/common_voice_9_0\", \"en\", split=\"validation\", use_auth_token=hf_auth_token\n",
    ")\n",
    "libri_clean_dev = load_dataset(\"librispeech_asr\", \"all\", split=\"validation.clean\")\n",
    "libri_other_dev = load_dataset(\"librispeech_asr\", \"all\", split=\"validation.other\")\n",
    "\n",
    "# for each of them then you can get the raw audio like this:\n",
    "audio_arrays = [e[\"array\"] for e in data[\"audio\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3c3f0496",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4b155379",
   "metadata": {},
   "outputs": [],
   "source": [
    "def _write_audios(\n",
    "    data, \n",
    "    dataset_name, \n",
    "    id_column=\"id\", \n",
    "    text_column=\"text\", \n",
    "    text_2_column=None, \n",
    "    clean_write=True, \n",
    "    base_dir=DATA_BASE_DIR,\n",
    "):\n",
    "    dataset_dir = os.path.join(base_dir, dataset_name)\n",
    "    if clean_write:\n",
    "        shutil.rmtree(dataset_dir, ignore_errors=True)\n",
    "        os.makedirs(dataset_dir, exist_ok=True)\n",
    "    ids = data[id_column]\n",
    "    texts = data[text_column]\n",
    "    audios = [\n",
    "        Audio.from_array_float(e[\"array\"], sample_rate=e[\"sampling_rate\"], max_allowed_val=3.0)\n",
    "        for e in data[\"audio\"]\n",
    "    ]\n",
    "    if text_2_column is not None:\n",
    "        texts_2 = data[text_2_column]\n",
    "    else:\n",
    "        texts_2 = []\n",
    "    metas = []\n",
    "    for n, (_id, text, audio) in enumerate(zip(ids, texts, audios)):\n",
    "        uid = str(uuid.uuid4())\n",
    "        to_fp = os.path.join(dataset_dir, f\"{uid}.wav\")\n",
    "        audio.convert(16_000, 2, 1).to_wav(to_fp)\n",
    "        m = {\n",
    "            \"dataset\": dataset_name,\n",
    "            \"index\": n,\n",
    "            \"id\": _id,\n",
    "            \"uid\": uid,\n",
    "            \"raw_text\": text,\n",
    "            \"uri\": to_fp,\n",
    "        }\n",
    "        if text_2_column is not None:\n",
    "            m[\"raw_text_2\"] = texts_2[n]\n",
    "        metas.append(m)\n",
    "    return metas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "2619d859",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "6acb63f909bd4ca8a179eaf431939e2f",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/16335 [00:00<?, ?ex/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ami_metas = _write_audios(ami_dev, \"ami\", id_column=\"audio_id\")\n",
    "ted_metas = _write_audios(ted_dev, \"ted\")\n",
    "vox_metas = _write_audios(\n",
    "    vox_dev, \"vox\", id_column=\"audio_id\", text_column=\"raw_text\", text_2_column=\"normalized_text\"\n",
    ")\n",
    "spgi_metas = _write_audios(spgi_dev, \"spgi\", id_column=\"wav_filename\", text_column=\"transcript\")\n",
    "giga_metas = _write_audios(giga_dev, \"giga\", id_column=\"segment_id\")\n",
    "def _make_id(row):\n",
    "    row[\"id\"] = row[\"source_id\"] + \"-\" + row[\"segment_id\"]\n",
    "    return row\n",
    "earnings22_dev = earnings22_dev.map(_make_id)\n",
    "earnings22_metas = _write_audios(earnings22_dev, \"earnings22\", text_column=\"sentence\")\n",
    "def _make_id(row):\n",
    "    row[\"id\"] = get_filename(row[\"path\"])\n",
    "    return row\n",
    "cv9_dev = cv9_dev.map(_make_id)\n",
    "cv9_metas = _write_audios(cv9_dev, \"cv9\", text_column=\"sentence\")\n",
    "libri_clean_metas = _write_audios(libri_clean_dev, \"libri_clean\")\n",
    "libri_other_metas = _write_audios(libri_other_dev, \"libri_other\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "d04ed475",
   "metadata": {},
   "outputs": [],
   "source": [
    "metadata = (\n",
    "    ami_metas + \n",
    "    ted_metas + \n",
    "    vox_metas + \n",
    "    spgi_metas + \n",
    "    giga_metas + \n",
    "    earnings22_metas + \n",
    "    cv9_metas + \n",
    "    libri_clean_metas + \n",
    "    libri_other_metas\n",
    ")\n",
    "with open(os.path.join(DATA_BASE_DIR, \"raw_metadata.json\"), \"w\") as f:\n",
    "    json.dump(metadata, f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9fff1db5",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d65c6a3c",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "95ba9d35",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "7ffcd132",
   "metadata": {},
   "source": [
    "## Do transcription"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "e9716000",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[NeMo W 2022-09-21 09:46:23 optimizers:77] Could not import distributed_fused_adam optimizer from Apex\n"
     ]
    }
   ],
   "source": [
    "from suno_utils.tasks.asr import transcribe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "id": "56eb4bde",
   "metadata": {},
   "outputs": [],
   "source": [
    "with open(os.path.join(DATA_BASE_DIR, \"raw_metadata.json\")) as f:\n",
    "    metadata = json.load(f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "30a92dfc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "a01004da0f4546778e145e596a88f27e",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Transcribing:   0%|          | 0/10757 [00:01<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "asr_out = transcribe([m[\"uri\"] for m in metadata])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "31b07118",
   "metadata": {},
   "outputs": [],
   "source": [
    "def _asr_normalize(text):\n",
    "    text = text.lower().strip()\n",
    "    text = re.sub(r\"[^a-z \\']\", \" \", text)\n",
    "    return normalize_whitespace(text)\n",
    "\n",
    "for m, asr in zip(metadata, asr_out):\n",
    "    m[\"asr\"] = _asr_normalize(asr)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "id": "449255c4",
   "metadata": {},
   "outputs": [],
   "source": [
    "with open(os.path.join(DATA_BASE_DIR, \"metadata.json\"), \"w\") as f:\n",
    "    json.dump(metadata, f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "id": "ca78af9f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# def _get_transcripts(data):\n",
    "#     sample_rate = data[0][\"audio\"][\"sampling_rate\"]\n",
    "#     audios = []\n",
    "#     for e in data:\n",
    "#         audio = Audio.from_array_float(e[\"audio\"][\"array\"], sample_rate=sample_rate)\n",
    "#         audios.append(audio)\n",
    "#     transcripts = transcribe(audios)\n",
    "#     return transcripts\n",
    "\n",
    "# ami_dev_asr = _get_transcripts(ami_dev)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "79e35cd0",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8cfec043",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "b61fba9c",
   "metadata": {},
   "source": [
    "## Score data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "85c281ba",
   "metadata": {},
   "outputs": [],
   "source": [
    "import nemo.collections.nlp as nemo_nlp\n",
    "\n",
    "from suno_utils.utils.display import suppress_logging\n",
    "from suno_utils.utils.metrics import get_wer\n",
    "from suno_utils.utils.text_normalizer import _normalize, _normalize_mp\n",
    "\n",
    "with suppress_logging():\n",
    "    punctuation_model = nemo_nlp.models.PunctuationCapitalizationModel.from_pretrained(\n",
    "        model_name=\"punctuation_en_bert\"\n",
    "    )\n",
    "    inverse_normalizer = InverseNormalizer(lang='en')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "id": "70985734",
   "metadata": {},
   "outputs": [],
   "source": [
    "with open(os.path.join(DATA_BASE_DIR, \"metadata.json\")) as f:\n",
    "    metadata = json.load(f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 177,
   "id": "ca6d0118",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|█████████████████████████████████| 86048/86048 [00:00<00:00, 183171.99it/s]\n"
     ]
    }
   ],
   "source": [
    "# do corpus specific fixing\n",
    "\n",
    "tedlium_contractions = {\" 's\", \" 't\", \" 're\", \" 've\", \" 'm\", \" 'll\", \" 'd\", \" 'clock\", \" 'all\"}\n",
    "gigaspeech_punctuation = {\" <comma>\": \",\", \" <period>\": \".\", \" <questionmark>\": \"?\", \" <exclamationpoint>\": \"!\"}\n",
    "\n",
    "def _fix_ami(text):\n",
    "    text = text.lower()\n",
    "    return text\n",
    "\n",
    "def _fix_ted(text):\n",
    "    # replace spaced apostrophes with un-spaced (it 's -> it's)\n",
    "    for contraction in tedlium_contractions:\n",
    "        text = text.replace(contraction, contraction[1:])\n",
    "    text = text.lower()\n",
    "    return text\n",
    "\n",
    "def _fix_giga(text):\n",
    "    # convert spelled out punctuation to symbolic form\n",
    "    for punctuation, replacement in gigaspeech_punctuation.items():\n",
    "        text = text.replace(punctuation, replacement)\n",
    "    text = text.lower()\n",
    "    return text\n",
    "\n",
    "def _fix_cv9(text):\n",
    "    if text.startswith('\"') and text.endswith('\"'):\n",
    "        # we can remove trailing quotation marks as they do not affect the transcription\n",
    "        text = text[1:-1]\n",
    "    # replace double quotation marks with single\n",
    "    text = text.replace('\"\"', '\"')\n",
    "    return text\n",
    "\n",
    "def _fix_libri(text):\n",
    "    text = text.lower()\n",
    "    return text\n",
    "\n",
    "def _preprocess(text):\n",
    "    text = re.sub(r\"\\<.*?\\>\", \" \", text)\n",
    "    text = re.sub(r\"\\[.*?\\]\", \" \", text)\n",
    "    text = text.replace(\"ignore_time_segment_in_scoring\", \" \")\n",
    "    text = normalize_whitespace(text)\n",
    "    return text\n",
    "\n",
    "for m in tqdm.tqdm(metadata):\n",
    "    if m[\"dataset\"] == \"ami\":\n",
    "        text_norm = m[\"raw_text\"]\n",
    "        text_norm = _fix_ami(text_norm)\n",
    "        text_norm = _preprocess(text_norm)\n",
    "        m[\"text\"] = text_norm\n",
    "    elif m[\"dataset\"] == \"ted\":\n",
    "        text_norm = m[\"raw_text\"]\n",
    "        text_norm = _fix_ted(text_norm)\n",
    "        text_norm = _preprocess(text_norm)\n",
    "        m[\"text\"] = text_norm\n",
    "    elif m[\"dataset\"] == \"vox\":\n",
    "        text_norm = m[\"raw_text_2\"]\n",
    "        text_norm = _preprocess(text_norm)\n",
    "        m[\"text\"] = text_norm\n",
    "    elif m[\"dataset\"] == \"spgi\":\n",
    "        text_norm = m[\"raw_text\"]\n",
    "        text_norm = _preprocess(text_norm)\n",
    "        m[\"text\"] = text_norm\n",
    "    elif m[\"dataset\"] == \"giga\":\n",
    "        text_norm = m[\"raw_text\"]\n",
    "        text_norm = _fix_giga(text_norm)                       \n",
    "        text_norm = _preprocess(text_norm)\n",
    "        m[\"text\"] = text_norm\n",
    "    elif m[\"dataset\"] == \"earnings22\":\n",
    "        text_norm = m[\"raw_text\"]\n",
    "        m[\"text\"] = text_norm\n",
    "    elif m[\"dataset\"] == \"cv9\":\n",
    "        text_norm = m[\"raw_text\"]\n",
    "        text_norm = _fix_cv9(text_norm)\n",
    "        text_norm = _preprocess(text_norm)\n",
    "        m[\"text\"] = text_norm\n",
    "    elif m[\"dataset\"] == \"libri_clean\":\n",
    "        text_norm = m[\"raw_text\"]\n",
    "        text_norm = _fix_libri(text_norm)\n",
    "        text_norm = _preprocess(text_norm)\n",
    "        m[\"text\"] = text_norm\n",
    "    elif m[\"dataset\"] == \"libri_other\":\n",
    "        text_norm = m[\"raw_text\"]\n",
    "        text_norm = _fix_libri(text_norm)\n",
    "        text_norm = _preprocess(text_norm)\n",
    "        m[\"text\"] = text_norm\n",
    "    else:\n",
    "        raise ValueError()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 179,
   "id": "e5475fe1",
   "metadata": {},
   "outputs": [],
   "source": [
    "# do audio normalization where needed\n",
    "to_norm_texts = []\n",
    "to_norm_asrs = []\n",
    "for m in metadata:\n",
    "    if m[\"dataset\"] in (\"spgi\", \"earnings22\"):\n",
    "        to_norm_texts.append([m[\"text\"]])\n",
    "        to_norm_asrs.append(m[\"asr\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 189,
   "id": "7954571f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.5 hours for 41954 files\n"
     ]
    }
   ],
   "source": [
    "t0 = time.time()\n",
    "audio_normed_texts = [e[0] for e in _normalize_mp(to_norm_texts, to_norm_asrs)]\n",
    "td = round((time.time() - t0) / 60 / 60, 1)\n",
    "print(td, \"hours for\", len(to_norm_texts), \"files\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 196,
   "id": "44f0ccd9",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 86048/86048 [00:01<00:00, 48946.84it/s]\n"
     ]
    }
   ],
   "source": [
    "## create text_norm\n",
    "def _base_normalize(text):\n",
    "    text = text.lower().strip()\n",
    "    text = re.sub(r\"[^a-z \\']\", \" \", text)\n",
    "    text = normalize_whitespace(text)\n",
    "    return text\n",
    "\n",
    "n_offs = 0\n",
    "for m in tqdm.tqdm(metadata):\n",
    "    if m[\"dataset\"] == \"ami\":\n",
    "        text_norm = m[\"text\"]\n",
    "        text_norm = _base_normalize(text_norm)\n",
    "        m[\"text_norm\"] = text_norm\n",
    "    elif m[\"dataset\"] == \"ted\":\n",
    "        text_norm = m[\"text\"]\n",
    "        text_norm = _base_normalize(text_norm)\n",
    "        m[\"text_norm\"] = text_norm\n",
    "    elif m[\"dataset\"] == \"vox\":\n",
    "        text_norm = m[\"raw_text_2\"]\n",
    "        text_norm = _base_normalize(text_norm)\n",
    "        m[\"text_norm\"] = text_norm\n",
    "    elif m[\"dataset\"] == \"spgi\":\n",
    "        text_norm = audio_normed_texts[n_offs]\n",
    "        text_norm = _base_normalize(text_norm)\n",
    "        m[\"text_norm\"] = text_norm\n",
    "        n_offs += 1\n",
    "    elif m[\"dataset\"] == \"giga\":\n",
    "        text_norm = m[\"text\"]\n",
    "        text_norm = _base_normalize(text_norm)\n",
    "        m[\"text_norm\"] = text_norm\n",
    "    elif m[\"dataset\"] == \"earnings22\":\n",
    "        text_norm = audio_normed_texts[n_offs]\n",
    "        text_norm = _base_normalize(text_norm)\n",
    "        m[\"text_norm\"] = text_norm\n",
    "        n_offs += 1\n",
    "    elif m[\"dataset\"] == \"cv9\":\n",
    "        text_norm = m[\"text\"]\n",
    "        text_norm = _base_normalize(text_norm)\n",
    "        m[\"text_norm\"] = text_norm\n",
    "    elif m[\"dataset\"] == \"libri_clean\":\n",
    "        text_norm = m[\"text\"]\n",
    "        text_norm = _base_normalize(text_norm)\n",
    "        m[\"text_norm\"] = text_norm\n",
    "    elif m[\"dataset\"] == \"libri_other\":\n",
    "        text_norm = m[\"text\"]\n",
    "        text_norm = _base_normalize(text_norm)\n",
    "        m[\"text_norm\"] = text_norm\n",
    "    else:\n",
    "        raise ValueError()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 243,
   "id": "6a583c78",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[NeMo I 2022-09-22 17:19:36 punctuation_capitalization_infer_dataset:91] Max length: 64\n",
      "[NeMo I 2022-09-22 17:19:36 data_preprocessing:404] Some stats of the lengths of the sequences:\n",
      "[NeMo I 2022-09-22 17:19:36 data_preprocessing:406] Min: 0 |                  Max: 143 |                  Mean: 15.53402500090061 |                  Median: 12.0\n",
      "[NeMo I 2022-09-22 17:19:36 data_preprocessing:412] 75 percentile: 23.00\n",
      "[NeMo I 2022-09-22 17:19:36 data_preprocessing:413] 99 percentile: 61.00\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 884/884 [00:25<00:00, 34.02batch/s]\n",
      "100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 86048/86048 [00:00<00:00, 2185170.32it/s]\n"
     ]
    }
   ],
   "source": [
    "# capitalize/punctuate and denormalize where necessary\n",
    "to_process_texts = []\n",
    "for m in metadata:\n",
    "    if m[\"dataset\"] in (\"ami\", \"ted\", \"vox\", \"giga\", \"libri_clean\", \"libri_other\"):\n",
    "        to_process_texts.append(m[\"text_norm\"])\n",
    "\n",
    "itn_texts = []\n",
    "for to_process_text in tqdm.tqdm(to_process_texts, disable=True):\n",
    "    itn_texts.append(inverse_normalizer.inverse_normalize(to_process_text, verbose=False))\n",
    "orthographic_texts = punctuation_model.add_punctuation_capitalization(itn_texts, batch_size=32)\n",
    "\n",
    "n_offs = 0\n",
    "for m in tqdm.tqdm(metadata):\n",
    "    if m[\"dataset\"] == \"ami\":\n",
    "        m[\"text\"] = orthographic_texts[n_offs]\n",
    "        n_offs += 1\n",
    "    elif m[\"dataset\"] == \"ted\":\n",
    "        m[\"text\"] = orthographic_texts[n_offs]\n",
    "        n_offs += 1\n",
    "    elif m[\"dataset\"] == \"vox\":\n",
    "        m[\"text\"] = orthographic_texts[n_offs]\n",
    "        n_offs += 1\n",
    "    elif m[\"dataset\"] == \"giga\":\n",
    "        m[\"text\"] = orthographic_texts[n_offs]\n",
    "        n_offs += 1\n",
    "    elif m[\"dataset\"] == \"libri_clean\":\n",
    "        m[\"text\"] = orthographic_texts[n_offs]\n",
    "        n_offs += 1\n",
    "    elif m[\"dataset\"] == \"libri_other\":\n",
    "        m[\"text\"] = orthographic_texts[n_offs]\n",
    "        n_offs += 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 244,
   "id": "c8201914",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 86048/86048 [00:01<00:00, 63041.62it/s]\n"
     ]
    }
   ],
   "source": [
    "## score\n",
    "for m in tqdm.tqdm(metadata):\n",
    "    m[\"wer\"] = get_wer(m[\"text_norm\"], m[\"asr\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 245,
   "id": "92951a9f",
   "metadata": {},
   "outputs": [],
   "source": [
    "with open(os.path.join(DATA_BASE_DIR, \"metadata_scored.json\"), \"w\") as f:\n",
    "    json.dump(metadata, f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9bcfc8f2",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "94d08cbd",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "e7de9d86",
   "metadata": {},
   "source": [
    "## (optional) investigate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "73f7f435",
   "metadata": {},
   "outputs": [],
   "source": [
    "with open(os.path.join(DATA_BASE_DIR, \"metadata_scored.json\")) as f:\n",
    "    metadata = json.load(f)\n",
    "df = pd.DataFrame(metadata)[[\"dataset\", \"index\", \"uri\", \"wer\", \"raw_text\", \"asr\", \"text\", \"text_norm\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 250,
   "id": "46663a5a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>dataset</th>\n",
       "      <th>index</th>\n",
       "      <th>uri</th>\n",
       "      <th>wer</th>\n",
       "      <th>raw_text</th>\n",
       "      <th>asr</th>\n",
       "      <th>text</th>\n",
       "      <th>text_norm</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ami</td>\n",
       "      <td>0</td>\n",
       "      <td>/mnt/data-ssd-1/data/academia/hf_paper/ami/1f3...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>HERE WE GO</td>\n",
       "      <td>here we go</td>\n",
       "      <td>Here we go.</td>\n",
       "      <td>here we go</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ami</td>\n",
       "      <td>1</td>\n",
       "      <td>/mnt/data-ssd-1/data/academia/hf_paper/ami/4cd...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>WELCOME EVERYBODY</td>\n",
       "      <td>welcome everybody</td>\n",
       "      <td>Welcome, everybody.</td>\n",
       "      <td>welcome everybody</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ami</td>\n",
       "      <td>2</td>\n",
       "      <td>/mnt/data-ssd-1/data/academia/hf_paper/ami/4de...</td>\n",
       "      <td>0.5</td>\n",
       "      <td>UM I'M ABIGAIL CLAFLIN</td>\n",
       "      <td>i'm abigail claughlin</td>\n",
       "      <td>Um, I'm Abigail Claflin.</td>\n",
       "      <td>um i'm abigail claflin</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  dataset  index                                                uri  wer  \\\n",
       "0     ami      0  /mnt/data-ssd-1/data/academia/hf_paper/ami/1f3...  0.0   \n",
       "1     ami      1  /mnt/data-ssd-1/data/academia/hf_paper/ami/4cd...  0.0   \n",
       "2     ami      2  /mnt/data-ssd-1/data/academia/hf_paper/ami/4de...  0.5   \n",
       "\n",
       "                 raw_text                    asr                      text  \\\n",
       "0              HERE WE GO             here we go               Here we go.   \n",
       "1       WELCOME EVERYBODY      welcome everybody       Welcome, everybody.   \n",
       "2  UM I'M ABIGAIL CLAFLIN  i'm abigail claughlin  Um, I'm Abigail Claflin.   \n",
       "\n",
       "                text_norm  \n",
       "0              here we go  \n",
       "1       welcome everybody  \n",
       "2  um i'm abigail claflin  "
      ]
     },
     "execution_count": 250,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 262,
   "id": "e3711a19",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>dataset</th>\n",
       "      <th>index</th>\n",
       "      <th>uri</th>\n",
       "      <th>wer</th>\n",
       "      <th>raw_text</th>\n",
       "      <th>asr</th>\n",
       "      <th>text</th>\n",
       "      <th>text_norm</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>6574</th>\n",
       "      <td>ami</td>\n",
       "      <td>6574</td>\n",
       "      <td>/mnt/data-ssd-1/data/academia/hf_paper/ami/979...</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>YEP</td>\n",
       "      <td>yes</td>\n",
       "      <td>Yep.</td>\n",
       "      <td>yep</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>966</th>\n",
       "      <td>ami</td>\n",
       "      <td>966</td>\n",
       "      <td>/mnt/data-ssd-1/data/academia/hf_paper/ami/2a6...</td>\n",
       "      <td>0.235294</td>\n",
       "      <td>UM AND YOU JUST HAVE THIS IT'S LIKE JUST A LON...</td>\n",
       "      <td>and you just have this and it's like just a lo...</td>\n",
       "      <td>Um, and you just have this? It's like just a l...</td>\n",
       "      <td>um and you just have this it's like just a lon...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12369</th>\n",
       "      <td>ami</td>\n",
       "      <td>12369</td>\n",
       "      <td>/mnt/data-ssd-1/data/academia/hf_paper/ami/3b4...</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>WELL UH FRUIT AND VEGETABLES YEAH</td>\n",
       "      <td>well fruit and vegetables</td>\n",
       "      <td>Well, uh, fruit and vegetables, Yeah.</td>\n",
       "      <td>well uh fruit and vegetables yeah</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10279</th>\n",
       "      <td>ami</td>\n",
       "      <td>10279</td>\n",
       "      <td>/mnt/data-ssd-1/data/academia/hf_paper/ami/dfe...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>ALSO THE ONE IN THE DARK</td>\n",
       "      <td>also the one in the dark</td>\n",
       "      <td>Also the one in the dark.</td>\n",
       "      <td>also the one in the dark</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4477</th>\n",
       "      <td>ami</td>\n",
       "      <td>4477</td>\n",
       "      <td>/mnt/data-ssd-1/data/academia/hf_paper/ami/74f...</td>\n",
       "      <td>0.111111</td>\n",
       "      <td>UM AND SO THAT MAKES I THINK EIGHTEEN PLACES</td>\n",
       "      <td>and so that makes i think eighteen places</td>\n",
       "      <td>Um, and so that makes I think 18 places.</td>\n",
       "      <td>um and so that makes i think eighteen places</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      dataset  index                                                uri  \\\n",
       "6574      ami   6574  /mnt/data-ssd-1/data/academia/hf_paper/ami/979...   \n",
       "966       ami    966  /mnt/data-ssd-1/data/academia/hf_paper/ami/2a6...   \n",
       "12369     ami  12369  /mnt/data-ssd-1/data/academia/hf_paper/ami/3b4...   \n",
       "10279     ami  10279  /mnt/data-ssd-1/data/academia/hf_paper/ami/dfe...   \n",
       "4477      ami   4477  /mnt/data-ssd-1/data/academia/hf_paper/ami/74f...   \n",
       "\n",
       "            wer                                           raw_text  \\\n",
       "6574   1.000000                                                YEP   \n",
       "966    0.235294  UM AND YOU JUST HAVE THIS IT'S LIKE JUST A LON...   \n",
       "12369  0.333333                  WELL UH FRUIT AND VEGETABLES YEAH   \n",
       "10279  0.000000                           ALSO THE ONE IN THE DARK   \n",
       "4477   0.111111       UM AND SO THAT MAKES I THINK EIGHTEEN PLACES   \n",
       "\n",
       "                                                     asr  \\\n",
       "6574                                                 yes   \n",
       "966    and you just have this and it's like just a lo...   \n",
       "12369                          well fruit and vegetables   \n",
       "10279                           also the one in the dark   \n",
       "4477           and so that makes i think eighteen places   \n",
       "\n",
       "                                                    text  \\\n",
       "6574                                                Yep.   \n",
       "966    Um, and you just have this? It's like just a l...   \n",
       "12369              Well, uh, fruit and vegetables, Yeah.   \n",
       "10279                          Also the one in the dark.   \n",
       "4477            Um, and so that makes I think 18 places.   \n",
       "\n",
       "                                               text_norm  \n",
       "6574                                                 yep  \n",
       "966    um and you just have this it's like just a lon...  \n",
       "12369                  well uh fruit and vegetables yeah  \n",
       "10279                           also the one in the dark  \n",
       "4477        um and so that makes i think eighteen places  "
      ]
     },
     "execution_count": 262,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df[\"dataset\"] == \"ami\"].sample(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 263,
   "id": "ea1a59d9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Well, uh, fruit and vegetables, Yeah.\n",
      "well uh fruit and vegetables yeah\n",
      "well fruit and vegetables\n"
     ]
    },
    {
     "data": {
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\"/>\n",
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       "</audio>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "row = df.iloc[12369]\n",
    "\n",
    "print(row[\"text\"])\n",
    "print(row[\"text_norm\"])\n",
    "print(row[\"asr\"])\n",
    "Audio.from_file(row[\"uri\"]).play()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bbf0cbed",
   "metadata": {},
   "source": [
    "NOTES\n",
    "\n",
    "AMI\n",
    "  okay -> ok?\n",
    "  yep -> yes?\n",
    "  partial words like 'becau yeah' need a -- "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 267,
   "id": "bfb7bf1d",
   "metadata": {},
   "outputs": [],
   "source": [
    "_df = df[df[\"dataset\"] == \"ami\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 270,
   "id": "16768fb1",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[NeMo W 2022-09-22 18:11:10 nemo_logging:349] /home/georg/venvs/ml/lib/python3.8/site-packages/IPython/core/magics/pylab.py:159: UserWarning: pylab import has clobbered these variables: ['f', 'random']\n",
      "    `%matplotlib` prevents importing * from pylab and numpy\n",
      "      warn(\"pylab import has clobbered these variables: %s\"  % clobbered +\n",
      "    \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Populating the interactive namespace from numpy and matplotlib\n"
     ]
    }
   ],
   "source": [
    "%pylab inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 278,
   "id": "1d320f62",
   "metadata": {},
   "outputs": [],
   "source": [
    "_df_mini = _df.sample(1000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 279,
   "id": "287fdc77",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x7f3cd13b2fd0>"
      ]
     },
     "execution_count": 279,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(_df_mini[\"raw_text\"].str.len().values, _df_mini[\"wer\"].values, alpha=0.5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 311,
   "id": "d2fd9666",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x7f3dcc6558b0>"
      ]
     },
     "execution_count": 311,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(_df[\"raw_text\"].str.len().values, _df[\"wer\"].values, alpha=0.2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 268,
   "id": "ec8997d7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>dataset</th>\n",
       "      <th>index</th>\n",
       "      <th>uid</th>\n",
       "      <th>uri</th>\n",
       "      <th>wer</th>\n",
       "      <th>raw_text</th>\n",
       "      <th>asr</th>\n",
       "      <th>text</th>\n",
       "      <th>text_norm</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ami</td>\n",
       "      <td>0</td>\n",
       "      <td>1f3000b1-c07f-45cb-84d0-c068fe12203a</td>\n",
       "      <td>/mnt/data-ssd-1/data/academia/hf_paper/ami/1f3...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>HERE WE GO</td>\n",
       "      <td>here we go</td>\n",
       "      <td>Here we go.</td>\n",
       "      <td>here we go</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ami</td>\n",
       "      <td>1</td>\n",
       "      <td>4cde37b6-caf8-46e5-a657-b16439f92b78</td>\n",
       "      <td>/mnt/data-ssd-1/data/academia/hf_paper/ami/4cd...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>WELCOME EVERYBODY</td>\n",
       "      <td>welcome everybody</td>\n",
       "      <td>Welcome, everybody.</td>\n",
       "      <td>welcome everybody</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ami</td>\n",
       "      <td>2</td>\n",
       "      <td>4de9e695-8be7-42db-ac6e-b0ed98add59c</td>\n",
       "      <td>/mnt/data-ssd-1/data/academia/hf_paper/ami/4de...</td>\n",
       "      <td>0.5</td>\n",
       "      <td>UM I'M ABIGAIL CLAFLIN</td>\n",
       "      <td>i'm abigail claughlin</td>\n",
       "      <td>Um, I'm Abigail Claflin.</td>\n",
       "      <td>um i'm abigail claflin</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ami</td>\n",
       "      <td>3</td>\n",
       "      <td>151afa7b-4767-42d1-82b1-33e970fdf7fa</td>\n",
       "      <td>/mnt/data-ssd-1/data/academia/hf_paper/ami/151...</td>\n",
       "      <td>0.2</td>\n",
       "      <td>YOU CAN CALL ME ABBIE</td>\n",
       "      <td>you can call me abby</td>\n",
       "      <td>You can call me Abbie.</td>\n",
       "      <td>you can call me abbie</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ami</td>\n",
       "      <td>4</td>\n",
       "      <td>98075ab0-539b-4e64-ba18-e0231d541d89</td>\n",
       "      <td>/mnt/data-ssd-1/data/academia/hf_paper/ami/980...</td>\n",
       "      <td>0.5</td>\n",
       "      <td>'S SEE</td>\n",
       "      <td>see</td>\n",
       "      <td>'s see.</td>\n",
       "      <td>'s see</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  dataset  index                                   uid  \\\n",
       "0     ami      0  1f3000b1-c07f-45cb-84d0-c068fe12203a   \n",
       "1     ami      1  4cde37b6-caf8-46e5-a657-b16439f92b78   \n",
       "2     ami      2  4de9e695-8be7-42db-ac6e-b0ed98add59c   \n",
       "3     ami      3  151afa7b-4767-42d1-82b1-33e970fdf7fa   \n",
       "4     ami      4  98075ab0-539b-4e64-ba18-e0231d541d89   \n",
       "\n",
       "                                                 uri  wer  \\\n",
       "0  /mnt/data-ssd-1/data/academia/hf_paper/ami/1f3...  0.0   \n",
       "1  /mnt/data-ssd-1/data/academia/hf_paper/ami/4cd...  0.0   \n",
       "2  /mnt/data-ssd-1/data/academia/hf_paper/ami/4de...  0.5   \n",
       "3  /mnt/data-ssd-1/data/academia/hf_paper/ami/151...  0.2   \n",
       "4  /mnt/data-ssd-1/data/academia/hf_paper/ami/980...  0.5   \n",
       "\n",
       "                 raw_text                    asr                      text  \\\n",
       "0              HERE WE GO             here we go               Here we go.   \n",
       "1       WELCOME EVERYBODY      welcome everybody       Welcome, everybody.   \n",
       "2  UM I'M ABIGAIL CLAFLIN  i'm abigail claughlin  Um, I'm Abigail Claflin.   \n",
       "3   YOU CAN CALL ME ABBIE   you can call me abby    You can call me Abbie.   \n",
       "4                  'S SEE                    see                   's see.   \n",
       "\n",
       "                text_norm  \n",
       "0              here we go  \n",
       "1       welcome everybody  \n",
       "2  um i'm abigail claflin  \n",
       "3   you can call me abbie  \n",
       "4                  's see  "
      ]
     },
     "execution_count": 268,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "767ea3c8",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "de7b5681",
   "metadata": {},
   "source": [
    "## Select data to annotate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 390,
   "id": "19d6ca79",
   "metadata": {},
   "outputs": [],
   "source": [
    "with open(os.path.join(DATA_BASE_DIR, \"metadata_scored.json\")) as f:\n",
    "    metadata = json.load(f)\n",
    "df = pd.DataFrame(metadata)[[\"dataset\", \"index\", \"uid\", \"uri\", \"wer\", \"raw_text\", \"asr\", \"text\", \"text_norm\"]]\n",
    "df[\"duration_s\"] = df[\"uri\"].apply(lambda x: Audio.get_details(x, attempt_using_header=True)[\"duration_s\"])\n",
    "df[\"is_clean\"] = True"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 391,
   "id": "4c33a493",
   "metadata": {},
   "outputs": [],
   "source": [
    "# label clean/other in libri\n",
    "df.loc[df[\"dataset\"] == \"libri_other\", \"is_clean\"] = False\n",
    "df.loc[df[\"dataset\"].isin([\"libri_clean\", \"libri_other\"]), \"dataset\"] = \"libri\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 392,
   "id": "8630e6e7",
   "metadata": {},
   "outputs": [],
   "source": [
    "# label clean/other in rest based on wer mean within duration buckets\n",
    "n_buckets = 5\n",
    "uid_is_clean_map = {}\n",
    "for dataset in set(df[\"dataset\"]) - set([\"libri\"]):\n",
    "    # get buckets\n",
    "    _df = df[df[\"dataset\"] == dataset].copy()\n",
    "    _df[\"tmp_bucket\"] = pd.qcut(_df[\"duration_s\"], n_buckets, labels=list(range(n_buckets))).values\n",
    "    # for each bucket sort by wer and split in half\n",
    "    for bucket_id in set(_df[\"tmp_bucket\"]):\n",
    "        __df = _df[_df[\"tmp_bucket\"] == bucket_id]\n",
    "        for uid in __df.sort_values(\"wer\").iloc[:__df.shape[0] // 2][\"uid\"].values:\n",
    "            uid_is_clean_map[uid] = True\n",
    "        for uid in __df.sort_values(\"wer\").iloc[__df.shape[0] // 2:][\"uid\"].values:\n",
    "            uid_is_clean_map[uid] = False\n",
    "#     # split by mean wer\n",
    "#     _df[\"tmp_wer_cut\"] = _df[\"tmp_bucket\"].map(_df.groupby(\"tmp_bucket\")[\"wer\"].mean()).astype(\"float\")\n",
    "#     _df.loc[_df[\"wer\"] > _df[\"tmp_wer_cut\"], \"is_clean\"] = False\n",
    "#     for _, row in _df.iterrows():\n",
    "#         uid_is_clean_map[row[\"uid\"]] = row[\"is_clean\"]\n",
    "\n",
    "df[\"is_clean\"] = df.apply(lambda x: uid_is_clean_map.get(x[\"uid\"], x[\"is_clean\"]), axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 393,
   "id": "f9162b2c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# save dataset\n",
    "df.to_csv(os.path.join(DATA_BASE_DIR, \"metadata_groups.csv\"), index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 394,
   "id": "7dc6281b",
   "metadata": {},
   "outputs": [],
   "source": [
    "# take 35 mins from each (8*2)\n",
    "min_duration_per_group_s = 35 * 60\n",
    "\n",
    "random.seed(6006)\n",
    "data = []\n",
    "for dataset in set(df[\"dataset\"]):\n",
    "    for is_clean in (True, False):\n",
    "        _df = df[(df[\"dataset\"] == dataset) & (df[\"is_clean\"] == is_clean)]\n",
    "        l = list(range(len(_df)))\n",
    "        random.shuffle(l)\n",
    "        offs_s = 0\n",
    "        for _, row in _df.iloc[l].iterrows():\n",
    "            data.append(row)\n",
    "            offs_s += row[\"duration_s\"]\n",
    "            if offs_s >= min_duration_per_group_s:\n",
    "                break\n",
    "        if offs_s < min_duration_per_group_s:\n",
    "            print(\"not enough samples found for\", dataset, is_clean)\n",
    "samples_df = pd.concat(data, axis=1).T.reset_index(drop=True)\n",
    "samples_df = samples_df.sort_values([\"dataset\", \"index\"]).reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 414,
   "id": "ae589081",
   "metadata": {},
   "outputs": [],
   "source": [
    "# save dataset\n",
    "samples_df.to_csv(os.path.join(DATA_BASE_DIR, \"to_annotate_samples.csv\"), index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ce0ed6d4",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4c3ff490",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e5752ded",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "43b3cf59",
   "metadata": {},
   "source": [
    "## (optional) verify grouping etc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 463,
   "id": "3c90d751",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>dataset</th>\n",
       "      <th>index</th>\n",
       "      <th>uid</th>\n",
       "      <th>uri</th>\n",
       "      <th>wer</th>\n",
       "      <th>raw_text</th>\n",
       "      <th>asr</th>\n",
       "      <th>text</th>\n",
       "      <th>text_norm</th>\n",
       "      <th>duration_s</th>\n",
       "      <th>is_clean</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ami</td>\n",
       "      <td>6</td>\n",
       "      <td>7d52b3b0-a467-4665-bd67-1adfa7107cb9</td>\n",
       "      <td>/mnt/data-ssd-1/data/academia/hf_paper/ami/7d5...</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>THERE WE GO</td>\n",
       "      <td>there you go</td>\n",
       "      <td>There we go.</td>\n",
       "      <td>there we go</td>\n",
       "      <td>1.13</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ami</td>\n",
       "      <td>31</td>\n",
       "      <td>c809f93c-df43-47b2-b615-978bc9e0bb9a</td>\n",
       "      <td>/mnt/data-ssd-1/data/academia/hf_paper/ami/c80...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>YEAH</td>\n",
       "      <td>yeah</td>\n",
       "      <td>Yeah.</td>\n",
       "      <td>yeah</td>\n",
       "      <td>0.86</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  dataset  index                                   uid  \\\n",
       "0     ami      6  7d52b3b0-a467-4665-bd67-1adfa7107cb9   \n",
       "1     ami     31  c809f93c-df43-47b2-b615-978bc9e0bb9a   \n",
       "\n",
       "                                                 uri       wer     raw_text  \\\n",
       "0  /mnt/data-ssd-1/data/academia/hf_paper/ami/7d5...  0.333333  THERE WE GO   \n",
       "1  /mnt/data-ssd-1/data/academia/hf_paper/ami/c80...  0.000000         YEAH   \n",
       "\n",
       "            asr          text    text_norm  duration_s  is_clean  \n",
       "0  there you go  There we go.  there we go        1.13     False  \n",
       "1          yeah         Yeah.         yeah        0.86      True  "
      ]
     },
     "execution_count": 463,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "samples_df = pd.read_csv(os.path.join(DATA_BASE_DIR, \"to_annotate_samples.csv\"))\n",
    "samples_df.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 469,
   "id": "4ab4b1ce",
   "metadata": {},
   "outputs": [],
   "source": [
    "# (samples_df.groupby([\"dataset\", \"is_clean\"])[\"duration_s\"].sum() / 60).round(1).rename(\"duration (mins)\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 470,
   "id": "a8e64424",
   "metadata": {},
   "outputs": [],
   "source": [
    "# samples_df.groupby([\"dataset\", \"is_clean\"])[\"wer\"].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 408,
   "id": "83460fad",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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\"/>\n",
       "  Your browser does not support the audio element.\n",
       "</audio>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "dataset                                                     ami\n",
       "index                                                      6562\n",
       "uid                        a43cab6d-1b4b-4c49-b653-e74a194a9960\n",
       "uri           /mnt/data-ssd-1/data/academia/hf_paper/ami/a43...\n",
       "wer                                                    0.333333\n",
       "raw_text      ABOUT UH MAFIA UH IT THAT'S WHY I THA THAT'S W...\n",
       "asr           about mefia that's why that that's why i didn'...\n",
       "text          About uh, mafia, uh, it, that's why I tha. tha...\n",
       "text_norm     about uh mafia uh it that's why i tha that's w...\n",
       "duration_s                                                 7.27\n",
       "is_clean                                                  False\n",
       "Name: 2976, dtype: object"
      ]
     },
     "execution_count": 408,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "row = samples_df.sample(1).iloc[0]\n",
    "Audio.from_file(row[\"uri\"]).play()\n",
    "row"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5ea66403",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3bd9fa2b",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f7cafc13",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "071d7867",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3bbebdc4",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a8b1e54d",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "d0a9518c",
   "metadata": {},
   "source": [
    "## Prep rev audio"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 426,
   "id": "23834464",
   "metadata": {},
   "outputs": [],
   "source": [
    "from suno_utils.utils.numbers import safe_round"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 488,
   "id": "3b1ef510",
   "metadata": {},
   "outputs": [],
   "source": [
    "REV_DIR = os.path.join(DATA_BASE_DIR, \"rev\")\n",
    "REV_AUDIO_DIR = os.path.join(REV_DIR, \"audio\")\n",
    "REV_TRANSCRIPT_DIR = os.path.join(REV_DIR, \"transcript\")\n",
    "\n",
    "os.makedirs(REV_DIR, exist_ok=True)\n",
    "os.makedirs(REV_AUDIO_DIR, exist_ok=True)\n",
    "os.makedirs(REV_TRANSCRIPT_DIR, exist_ok=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 425,
   "id": "67af1ed6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "9.4 hours\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>dataset</th>\n",
       "      <th>index</th>\n",
       "      <th>uid</th>\n",
       "      <th>uri</th>\n",
       "      <th>wer</th>\n",
       "      <th>raw_text</th>\n",
       "      <th>asr</th>\n",
       "      <th>text</th>\n",
       "      <th>text_norm</th>\n",
       "      <th>duration_s</th>\n",
       "      <th>is_clean</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ami</td>\n",
       "      <td>6</td>\n",
       "      <td>7d52b3b0-a467-4665-bd67-1adfa7107cb9</td>\n",
       "      <td>/mnt/data-ssd-1/data/academia/hf_paper/ami/7d5...</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>THERE WE GO</td>\n",
       "      <td>there you go</td>\n",
       "      <td>There we go.</td>\n",
       "      <td>there we go</td>\n",
       "      <td>1.13</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ami</td>\n",
       "      <td>31</td>\n",
       "      <td>c809f93c-df43-47b2-b615-978bc9e0bb9a</td>\n",
       "      <td>/mnt/data-ssd-1/data/academia/hf_paper/ami/c80...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>YEAH</td>\n",
       "      <td>yeah</td>\n",
       "      <td>Yeah.</td>\n",
       "      <td>yeah</td>\n",
       "      <td>0.86</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  dataset  index                                   uid  \\\n",
       "0     ami      6  7d52b3b0-a467-4665-bd67-1adfa7107cb9   \n",
       "1     ami     31  c809f93c-df43-47b2-b615-978bc9e0bb9a   \n",
       "\n",
       "                                                 uri       wer     raw_text  \\\n",
       "0  /mnt/data-ssd-1/data/academia/hf_paper/ami/7d5...  0.333333  THERE WE GO   \n",
       "1  /mnt/data-ssd-1/data/academia/hf_paper/ami/c80...  0.000000         YEAH   \n",
       "\n",
       "            asr          text    text_norm  duration_s  is_clean  \n",
       "0  there you go  There we go.  there we go        1.13     False  \n",
       "1          yeah         Yeah.         yeah        0.86      True  "
      ]
     },
     "execution_count": 425,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "samples_df = pd.read_csv(os.path.join(DATA_BASE_DIR, \"to_annotate_samples.csv\"))\n",
    "print(round(samples_df[\"duration_s\"].sum() / 60 / 60, 1), \"hours\")\n",
    "samples_df.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 434,
   "id": "da93c8fc",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 8/8 [00:01<00:00,  4.35it/s]\n"
     ]
    }
   ],
   "source": [
    "INDICATOR_AUDIO_DIR = \"/home/georg/notebooks/customers/sanas/audio_indicators/\"\n",
    "\n",
    "all_audio_segments = {}\n",
    "all_segments_meta = {}\n",
    "for dataset in tqdm.tqdm(set(samples_df[\"dataset\"])):\n",
    "    for is_clean in (True, False):\n",
    "        group_samples_df = samples_df[(samples_df[\"dataset\"] == dataset) & (samples_df[\"is_clean\"] == is_clean)]\n",
    "        audio_segments = []\n",
    "        segments_meta = []\n",
    "        for n, (_, row) in enumerate(group_samples_df.iterrows()):\n",
    "            indicator_str = str(n).zfill(2)\n",
    "            indicator_duration_s = 0\n",
    "            for c in indicator_str:\n",
    "                indicator_audio = Audio.from_file(\n",
    "                    os.path.join(INDICATOR_AUDIO_DIR, f\"{c}_fast.wav\"), sample_rate=16_000, byte_width=2,\n",
    "                )\n",
    "                indicator_duration_s += indicator_audio.duration_s\n",
    "                audio_segments.append(indicator_audio)\n",
    "            segments_meta.append({\n",
    "                \"segment_number\": n,\n",
    "                \"type\": \"indicator\",\n",
    "                \"duration_s\": safe_round(indicator_duration_s),\n",
    "                \"indicator_str\": indicator_str,\n",
    "            })\n",
    "            silence_audio = Audio.from_array(np.zeros(8_000, dtype=np.int16), 16_000)\n",
    "            audio_segments.append(silence_audio)\n",
    "            segments_meta.append({\n",
    "                \"segment_number\": n,\n",
    "                \"type\": \"silence\",\n",
    "                \"duration_s\": 0.5,\n",
    "            })\n",
    "            audio = Audio.from_file(row[\"uri\"])\n",
    "            audio_segments.append(audio)\n",
    "            segments_meta.append({\n",
    "                \"segment_number\": n,\n",
    "                \"type\": \"speech\",\n",
    "                \"duration_s\": safe_round(audio.duration_s),\n",
    "                \"uid\": row[\"uid\"],\n",
    "            })\n",
    "            silence_audio = Audio.from_array(np.zeros(8_000, dtype=np.int16), 16_000)\n",
    "            audio_segments.append(silence_audio)\n",
    "            segments_meta.append({\n",
    "                \"segment_number\": n,\n",
    "                \"type\": \"silence\",\n",
    "                \"duration_s\": 0.5,\n",
    "            })\n",
    "        tag_str = \"clean\" if is_clean else \"other\"\n",
    "        all_audio_segments[f\"{dataset}_{tag_str}\"] = Audio.concatenate(audio_segments)\n",
    "        all_segments_meta[f\"{dataset}_{tag_str}\"] = segments_meta"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 445,
   "id": "fae71951",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ted_clean - 41.3 mins\n",
      "ted_other - 41.2 mins\n",
      "vox_clean - 41.4 mins\n",
      "vox_other - 41.6 mins\n",
      "earnings22_clean - 44.3 mins\n",
      "earnings22_other - 43.9 mins\n",
      "giga_clean - 44.5 mins\n",
      "giga_other - 45.1 mins\n",
      "ami_clean - 62.3 mins\n",
      "ami_other - 62.3 mins\n",
      "cv9_clean - 45.9 mins\n",
      "cv9_other - 46.0 mins\n",
      "spgi_clean - 42.2 mins\n",
      "spgi_other - 42.1 mins\n",
      "libri_clean - 44.2 mins\n",
      "libri_other - 45.8 mins\n"
     ]
    }
   ],
   "source": [
    "for group_tag, audio_rev in all_audio_segments.items():\n",
    "    audio_rev.to_mp3(os.path.join(REV_AUDIO_DIR, f\"{group_tag}.mp3\"))\n",
    "    print(group_tag, \"-\", round(audio_rev.duration_s / 60, 1), \"mins\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 451,
   "id": "876d37ae",
   "metadata": {},
   "outputs": [],
   "source": [
    "with open(os.path.join(REV_DIR, \"concat_meta.json\"), \"w\") as f:\n",
    "    json.dump(all_segments_meta, f)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2e017ad4",
   "metadata": {},
   "source": [
    "### send to rev"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 449,
   "id": "f0cbf503",
   "metadata": {},
   "outputs": [],
   "source": [
    "from suno_utils.web.rev import get_auth_string, upload_file, make_order #, make_cc_order\n",
    "\n",
    "with open(\"/home/georg/.secrets/secrets.json\") as f:\n",
    "    secrets = json.load(f)\n",
    "    \n",
    "CLIENT_API_KEY = secrets[\"REV_CLIENT_API_KEY\"]\n",
    "USER_API_KEY = secrets[\"REV_USER_API_KEY\"]\n",
    "AUTH_STR = get_auth_string(CLIENT_API_KEY, USER_API_KEY)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 453,
   "id": "896be07f",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 16/16 [03:29<00:00, 13.10s/it]\n"
     ]
    }
   ],
   "source": [
    "order_items = []\n",
    "for group_tag in tqdm.tqdm(all_segments_meta.keys()):\n",
    "    filepath = os.path.join(REV_AUDIO_DIR, f\"{group_tag}.mp3\")\n",
    "    media_loc = upload_file(AUTH_STR, filepath, file_ref_str=group_tag)\n",
    "    order_items.append({\n",
    "        \"media_loc\": media_loc,\n",
    "        \"hotwords\": [],\n",
    "        \"duration_s\": Audio.get_details(filepath)[\"duration_s\"],\n",
    "    })"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 457,
   "id": "eb51cb48",
   "metadata": {},
   "outputs": [],
   "source": [
    "with open(os.path.join(REV_DIR, \"01_order_items.json\"), \"w\") as f:\n",
    "    json.dump(order_items, f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 456,
   "id": "12cc4955",
   "metadata": {},
   "outputs": [],
   "source": [
    "order_number = make_order(AUTH_STR, order_items, order_ref_str=\"hf_data\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 460,
   "id": "b7392fd2",
   "metadata": {},
   "outputs": [],
   "source": [
    "with open(os.path.join(REV_DIR, \"02_order_number.txt\"), \"w\") as f:\n",
    "    f.write(order_number)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1ddfa180",
   "metadata": {},
   "source": [
    "### get from rev"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 471,
   "id": "e8b59ece",
   "metadata": {},
   "outputs": [],
   "source": [
    "from suno_utils.web.rev import get_auth_string, get_finished_order, get_transcript\n",
    "\n",
    "with open(\"/home/georg/.secrets/secrets.json\") as f:\n",
    "    secrets = json.load(f)\n",
    "    \n",
    "CLIENT_API_KEY = secrets[\"REV_CLIENT_API_KEY\"]\n",
    "USER_API_KEY = secrets[\"REV_USER_API_KEY\"]\n",
    "AUTH_STR = get_auth_string(CLIENT_API_KEY, USER_API_KEY)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 477,
   "id": "9e4e40af",
   "metadata": {},
   "outputs": [],
   "source": [
    "with open(os.path.join(REV_DIR, \"02_order_number.txt\")) as f:\n",
    "    order_number = f.read()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 496,
   "id": "d2a371b5",
   "metadata": {},
   "outputs": [],
   "source": [
    "# # grab while still in progress\n",
    "# from suno_utils.web.rev import _get_order_details, _parse_order_response\n",
    "# order_details = _get_order_details(AUTH_STR, order_number)\n",
    "# _, transcript_metas = _parse_order_response(order_details)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 546,
   "id": "9275ae0d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# grab all of it\n",
    "transcript_metas = get_finished_order(AUTH_STR, order_number, blocking=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 547,
   "id": "df28d887",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 16/16 [00:04<00:00,  3.84it/s]\n"
     ]
    }
   ],
   "source": [
    "for transcript_meta in tqdm.tqdm(transcript_metas):\n",
    "    transcript_filepath = os.path.join(REV_TRANSCRIPT_DIR, transcript_meta[\"uuid\"] + \".json\")\n",
    "    if os.path.exists(transcript_filepath):\n",
    "        continue\n",
    "    transcript = get_transcript(AUTH_STR, transcript_meta)\n",
    "    with open(transcript_filepath, \"w\") as f:\n",
    "        json.dump(transcript, f)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b86d1519",
   "metadata": {},
   "source": [
    "### parse output"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 467,
   "id": "d50b0991",
   "metadata": {},
   "outputs": [],
   "source": [
    "from suno_utils.web.rev import parse_transcript\n",
    "from suno_utils.customers.sanas.pipeline import get_segments"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 468,
   "id": "732b8bf4",
   "metadata": {},
   "outputs": [],
   "source": [
    "with open(os.path.join(REV_DIR, f\"concat_meta.json\")) as f:\n",
    "    rev_audio_meta = json.load(f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 480,
   "id": "00e04fcf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "202/202 retained for ted_clean\n",
      "198/200 retained for ted_other\n",
      "207/207 retained for vox_clean\n",
      "215/215 retained for vox_other\n",
      "294/294 retained for earnings22_clean\n",
      "283/283 retained for earnings22_other\n",
      "299/299 retained for giga_clean\n",
      "321/321 retained for giga_other\n",
      "826/838 retained for ami_clean\n",
      "829/837 retained for ami_other\n",
      "342/342 retained for cv9_clean\n",
      "344/346 retained for cv9_other\n",
      "233/233 retained for spgi_clean\n",
      "229/229 retained for spgi_other\n",
      "290/290 retained for libri_clean\n",
      "337/337 retained for libri_other\n"
     ]
    }
   ],
   "source": [
    "transcripts_container = {}\n",
    "for group_tag, segments_meta in rev_audio_meta.items():\n",
    "    transcript_filepath = os.path.join(REV_TRANSCRIPT_DIR, f\"{group_tag}.json\")\n",
    "    if not os.path.exists(transcript_filepath):\n",
    "        print(f\"skipping {group_tag}...\")\n",
    "        continue\n",
    "    with open(transcript_filepath) as f:\n",
    "        raw_transcript = json.load(f)\n",
    "    transcript = parse_transcript(\n",
    "        raw_transcript, anonymize_speakers=True\n",
    "    )\n",
    "    n_segments = segments_meta[-1][\"segment_number\"] + 1\n",
    "    indexed_token_segments = get_segments(transcript, n_segments)\n",
    "    print(\"{}/{} retained for {}\".format(len(indexed_token_segments), n_segments, group_tag))\n",
    "#     if n_segments > len(indexed_token_segments):\n",
    "#         print(\"missing\", set(range(n_segments)) - set([e[0] for e in indexed_token_segments]))\n",
    "    segment_uid_map = {}\n",
    "    for m in segments_meta:\n",
    "        if m[\"type\"] == \"speech\":\n",
    "            segment_uid_map[m[\"segment_number\"]] = m[\"uid\"]\n",
    "    for segment_nr, tokens in indexed_token_segments:\n",
    "        uid = segment_uid_map[segment_nr]\n",
    "        transcripts_container[uid] = tokens.text"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 557,
   "id": "0621b50f",
   "metadata": {},
   "outputs": [],
   "source": [
    "with open(os.path.join(REV_DIR, \"transcripts.json\"), \"w\") as f:\n",
    "    json.dump(transcripts_container, f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "77447241",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "86a26d32",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7733c0f7",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "ddce4248",
   "metadata": {},
   "source": [
    "## Assemble everything together"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 605,
   "id": "34757776",
   "metadata": {},
   "outputs": [],
   "source": [
    "from suno_utils.utils.text_normalizer import normalize_mp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 588,
   "id": "0124d9a9",
   "metadata": {},
   "outputs": [],
   "source": [
    "with open(os.path.join(REV_DIR, \"transcripts.json\")) as f:\n",
    "    segment_transcripts = json.load(f)\n",
    "# some still have the number infront\n",
    "segment_transcripts = {\n",
    "    k: re.sub(r\"^[0-9]{2,3}\\.\\s*\", \"\", v) for k, v in segment_transcripts.items()\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 590,
   "id": "bc561855",
   "metadata": {},
   "outputs": [],
   "source": [
    "segments_df = pd.read_csv(os.path.join(DATA_BASE_DIR, \"to_annotate_samples.csv\"))\n",
    "segments_df[\"group_tag\"] = (\n",
    "    segments_df[\"dataset\"] + \"_\" + segments_df[\"is_clean\"].apply(lambda x: \"clean\" if x else \"other\")\n",
    ")\n",
    "segments_df = segments_df.drop(\"is_clean\", axis=1)\n",
    "segments_df[\"rev_text\"] = segments_df[\"uid\"].map(segment_transcripts)\n",
    "segments_df = segments_df.dropna(subset=[\"rev_text\"]).reset_index(drop=True)\n",
    "segments_df = segments_df.fillna(\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 613,
   "id": "869f864d",
   "metadata": {},
   "outputs": [],
   "source": [
    "out = normalize_mp(\n",
    "    [Tokens.from_text(s) for s in segments_df[\"rev_text\"].tolist()],\n",
    "    segments_df[\"asr\"].tolist(),\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 614,
   "id": "6989b537",
   "metadata": {},
   "outputs": [],
   "source": [
    "segments_df[\"rev_text_norm\"] = [e.plaintext for e in out]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 616,
   "id": "f819ad5f",
   "metadata": {},
   "outputs": [],
   "source": [
    "segments_df.to_csv(os.path.join(DATA_BASE_DIR, \"rev_annotated_samples.csv\"), index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f7dc4af6",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "663ba91b",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "c07655f0",
   "metadata": {},
   "source": [
    "## Check auto-matching and send rest for annotation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 454,
   "id": "ebcb97bd",
   "metadata": {},
   "outputs": [],
   "source": [
    "with open(\"ami_hand_labels.json\") as f:\n",
    "    fixed_segments = json.load(f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 455,
   "id": "fd09bcb4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>dataset</th>\n",
       "      <th>index</th>\n",
       "      <th>uid</th>\n",
       "      <th>uri</th>\n",
       "      <th>wer</th>\n",
       "      <th>raw_text</th>\n",
       "      <th>asr</th>\n",
       "      <th>text</th>\n",
       "      <th>text_norm</th>\n",
       "      <th>duration_s</th>\n",
       "      <th>group_tag</th>\n",
       "      <th>rev_text</th>\n",
       "      <th>rev_text_norm</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ami</td>\n",
       "      <td>6</td>\n",
       "      <td>7d52b3b0-a467-4665-bd67-1adfa7107cb9</td>\n",
       "      <td>/mnt/data-ssd-1/data/academia/hf_paper/ami/7d5...</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>THERE WE GO</td>\n",
       "      <td>there you go</td>\n",
       "      <td>There we go.</td>\n",
       "      <td>there we go</td>\n",
       "      <td>1.13</td>\n",
       "      <td>ami_other</td>\n",
       "      <td>There we go.</td>\n",
       "      <td>there we go</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ami</td>\n",
       "      <td>31</td>\n",
       "      <td>c809f93c-df43-47b2-b615-978bc9e0bb9a</td>\n",
       "      <td>/mnt/data-ssd-1/data/academia/hf_paper/ami/c80...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>YEAH</td>\n",
       "      <td>yeah</td>\n",
       "      <td>Yeah.</td>\n",
       "      <td>yeah</td>\n",
       "      <td>0.86</td>\n",
       "      <td>ami_clean</td>\n",
       "      <td>Yeah.</td>\n",
       "      <td>yeah</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  dataset  index                                   uid  \\\n",
       "0     ami      6  7d52b3b0-a467-4665-bd67-1adfa7107cb9   \n",
       "1     ami     31  c809f93c-df43-47b2-b615-978bc9e0bb9a   \n",
       "\n",
       "                                                 uri       wer     raw_text  \\\n",
       "0  /mnt/data-ssd-1/data/academia/hf_paper/ami/7d5...  0.333333  THERE WE GO   \n",
       "1  /mnt/data-ssd-1/data/academia/hf_paper/ami/c80...  0.000000         YEAH   \n",
       "\n",
       "            asr          text    text_norm  duration_s  group_tag  \\\n",
       "0  there you go  There we go.  there we go        1.13  ami_other   \n",
       "1          yeah         Yeah.         yeah        0.86  ami_clean   \n",
       "\n",
       "       rev_text rev_text_norm  \n",
       "0  There we go.   there we go  \n",
       "1         Yeah.          yeah  "
      ]
     },
     "execution_count": 455,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "segments_df = pd.read_csv(os.path.join(DATA_BASE_DIR, \"rev_annotated_samples.csv\"))\n",
    "segments_df = segments_df.fillna(\"\")\n",
    "segments_df.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 457,
   "id": "fdd91a49",
   "metadata": {},
   "outputs": [],
   "source": [
    "def _setify(s):\n",
    "    s = re.sub(r\"\\[.+?\\]\", \" \", s.lower())\n",
    "    s = re.sub(r\"[^a-z0-9\\']\", \" \", s.lower())\n",
    "    s = normalize_whitespace(s)\n",
    "    return set(s.split())\n",
    "\n",
    "\n",
    "to_consolidate_df = segments_df[\n",
    "    (~segments_df[\"uid\"].isin(set(fixed_segments.keys()))) &\n",
    "    ((segments_df[\"text\"].apply(_setify) - segments_df[\"rev_text\"].apply(_setify)).str.len() != 0)\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 218,
   "id": "474ecd3a",
   "metadata": {},
   "outputs": [],
   "source": [
    "to_consolidate_df.to_csv(os.path.join(DATA_BASE_DIR, \"to_consolidate_samples.csv\"), index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 219,
   "id": "4ee426c2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "5.6 hours to annotate in total\n"
     ]
    }
   ],
   "source": [
    "n0 = round(to_consolidate_df[\"duration_s\"].sum() / 60 / 60, 1)\n",
    "print(\"{} hours to annotate in total\".format(n0))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 220,
   "id": "e089ce3a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ami_clean: 14.8 mins to annotate\n",
      "ami_other: 26.8 mins to annotate\n",
      "cv9_clean: 14.0 mins to annotate\n",
      "cv9_other: 29.9 mins to annotate\n",
      "earnings22_clean: 16.5 mins to annotate\n",
      "earnings22_other: 31.3 mins to annotate\n",
      "giga_clean: 19.9 mins to annotate\n",
      "giga_other: 28.8 mins to annotate\n",
      "libri_clean: 18.9 mins to annotate\n",
      "libri_other: 20.3 mins to annotate\n",
      "spgi_clean: 14.1 mins to annotate\n",
      "spgi_other: 22.3 mins to annotate\n",
      "ted_clean: 16.6 mins to annotate\n",
      "ted_other: 24.8 mins to annotate\n",
      "vox_clean: 25.1 mins to annotate\n",
      "vox_other: 11.6 mins to annotate\n"
     ]
    }
   ],
   "source": [
    "for group_tag in sorted(set(to_consolidate_df[\"group_tag\"])):\n",
    "    df = to_consolidate_df[to_consolidate_df[\"group_tag\"] == group_tag]\n",
    "    n0 = round(df[\"duration_s\"].sum() / 60, 1)\n",
    "    print(\"{}: {} mins to annotate\".format(group_tag, n0))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b3d3fd0c",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "558217cd",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "992b1c55",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "8dbf702c",
   "metadata": {},
   "source": [
    "## Send for annotation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "id": "5ad3efb8",
   "metadata": {},
   "outputs": [],
   "source": [
    "PROJECT_ID = \"3d6fd2b7-48eb-40ac-a740-4b5a1bdb33ef\"\n",
    "CONSOLITDATION_SAMPLES_DIR = os.path.join(DATA_BASE_DIR, PROJECT_ID)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 221,
   "id": "261739b7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>dataset</th>\n",
       "      <th>index</th>\n",
       "      <th>uid</th>\n",
       "      <th>uri</th>\n",
       "      <th>wer</th>\n",
       "      <th>raw_text</th>\n",
       "      <th>asr</th>\n",
       "      <th>text</th>\n",
       "      <th>text_norm</th>\n",
       "      <th>duration_s</th>\n",
       "      <th>group_tag</th>\n",
       "      <th>rev_text</th>\n",
       "      <th>rev_text_norm</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ami</td>\n",
       "      <td>35</td>\n",
       "      <td>32159438-2286-4913-baf0-1a537a2bf553</td>\n",
       "      <td>/mnt/data-ssd-1/data/academia/hf_paper/ami/321...</td>\n",
       "      <td>0.571429</td>\n",
       "      <td>DOES ANYONE KNOW WHAT THEY WANNA DRAW</td>\n",
       "      <td>so anyone know what they want to traw</td>\n",
       "      <td>Does anyone know what they wanna draw?</td>\n",
       "      <td>does anyone know what they wanna draw</td>\n",
       "      <td>2.27</td>\n",
       "      <td>ami_other</td>\n",
       "      <td>Does anyone know what they want to draw? [laug...</td>\n",
       "      <td>does anyone know what they want to draw</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ami</td>\n",
       "      <td>43</td>\n",
       "      <td>ae0947e0-e373-473d-b60d-91927118b437</td>\n",
       "      <td>/mnt/data-ssd-1/data/academia/hf_paper/ami/ae0...</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>YES</td>\n",
       "      <td></td>\n",
       "      <td>Yes.</td>\n",
       "      <td>yes</td>\n",
       "      <td>0.16</td>\n",
       "      <td>ami_other</td>\n",
       "      <td>[inaudible]</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  dataset  index                                   uid  \\\n",
       "0     ami     35  32159438-2286-4913-baf0-1a537a2bf553   \n",
       "1     ami     43  ae0947e0-e373-473d-b60d-91927118b437   \n",
       "\n",
       "                                                 uri       wer  \\\n",
       "0  /mnt/data-ssd-1/data/academia/hf_paper/ami/321...  0.571429   \n",
       "1  /mnt/data-ssd-1/data/academia/hf_paper/ami/ae0...  1.000000   \n",
       "\n",
       "                                raw_text  \\\n",
       "0  DOES ANYONE KNOW WHAT THEY WANNA DRAW   \n",
       "1                                    YES   \n",
       "\n",
       "                                     asr  \\\n",
       "0  so anyone know what they want to traw   \n",
       "1                                          \n",
       "\n",
       "                                     text  \\\n",
       "0  Does anyone know what they wanna draw?   \n",
       "1                                    Yes.   \n",
       "\n",
       "                               text_norm  duration_s  group_tag  \\\n",
       "0  does anyone know what they wanna draw        2.27  ami_other   \n",
       "1                                    yes        0.16  ami_other   \n",
       "\n",
       "                                            rev_text  \\\n",
       "0  Does anyone know what they want to draw? [laug...   \n",
       "1                                        [inaudible]   \n",
       "\n",
       "                             rev_text_norm  \n",
       "0  does anyone know what they want to draw  \n",
       "1                                           "
      ]
     },
     "execution_count": 221,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "to_consolidate_df = pd.read_csv(os.path.join(DATA_BASE_DIR, \"to_consolidate_samples.csv\"))\n",
    "to_consolidate_df = to_consolidate_df.fillna(\"\")\n",
    "to_consolidate_df.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "id": "0a182c3f",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 2804/2804 [00:00<00:00, 4749.80it/s]\n"
     ]
    }
   ],
   "source": [
    "# move files to a folder\n",
    "shutil.rmtree(CONSOLITDATION_SAMPLES_DIR, ignore_errors=True)\n",
    "os.makedirs(CONSOLITDATION_SAMPLES_DIR, exist_ok=True)\n",
    "for _, row in tqdm.tqdm(to_consolidate_df.iterrows(), total=to_consolidate_df.shape[0]):\n",
    "    shutil.copy(row[\"uri\"], os.path.join(CONSOLITDATION_SAMPLES_DIR, f\"{row['uid']}.wav\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "id": "5a261a15",
   "metadata": {},
   "outputs": [],
   "source": [
    "# cd /mnt/data-ssd-1/data/academia/hf_paper\n",
    "# s4cmd dsync /mnt/data-ssd-1/data/academia/hf_paper/3d6fd2b7-48eb-40ac-a740-4b5a1bdb33ef s3://suno-data-uploads/studio/projects/3d6fd2b7-48eb-40ac-a740-4b5a1bdb33ef"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "69f110ee",
   "metadata": {},
   "outputs": [],
   "source": [
    "from suno_utils.labeler.client import SunoAPIClient"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "id": "fdb4bbbb",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Token here https://datasets.suno.ai/console/settings\n",
    "api = SunoAPIClient(api_url='https://datasets-api.suno.ai/graphql/', token='bd60a8ce56e0407085bd7c59b774c4d0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 229,
   "id": "317b8059",
   "metadata": {},
   "outputs": [],
   "source": [
    "task_config_meta = {\n",
    "    \"blocks\": [\n",
    "        {\"data\": {\"key\": \"url\"}, \"type\": \"audio\", \"props\": {\"complex\": True}},\n",
    "        {\"data\": {\"key\": \"rev_text\"}, \"type\": \"markdown\"},\n",
    "        {\"data\": {\"key\": \"text\"}, \"type\": \"textarea\", \"props\": {\"placeholder\": \"\"}}, \n",
    "#         {\"data\": {\"key\": \"rev_text_norm\"}, \"type\": \"markdown\"},\n",
    "#         {\"data\": {\"key\": \"text_norm\"}, \"type\": \"textarea\", \"props\": {\"placeholder\": \"\"}}\n",
    "    ]\n",
    "}\n",
    "\n",
    "save_data = {}\n",
    "for group_tag in sorted(set(to_consolidate_df[\"group_tag\"])):\n",
    "    _df = to_consolidate_df[to_consolidate_df[\"group_tag\"] == group_tag]\n",
    "    \n",
    "    p = api.create_project(name=group_tag)\n",
    "    \n",
    "    datums = []\n",
    "    for _, row in _df.iterrows():\n",
    "        datums.append({\n",
    "            \"metadata\": {\n",
    "                \"type\": \"audio\",\n",
    "                \"text\": row[\"text\"],\n",
    "#                 \"text_norm\": row[\"text_norm\"],\n",
    "                \"rev_text\": row[\"rev_text\"],\n",
    "#                 \"rev_text_norm\": row[\"rev_text_norm\"],\n",
    "            },\n",
    "            \"externalId\": row[\"uid\"],\n",
    "            \"storageKey\": f\"studio/projects/{PROJECT_ID}/{row['uid']}.wav\"\n",
    "        })\n",
    "    datums_out = p.add_data(datums)\n",
    "    \n",
    "    # Once created, you can go https://console.suno.ai/ and click on the project and start labeling.\n",
    "    task_out = p.add_task_config({'name': 'HF fixup', 'metadata': task_config_meta})\n",
    "    \n",
    "    save_data[group_tag] = {\n",
    "        \"project_id\": p.id,\n",
    "        \"task_id\": task_out[\"id\"],\n",
    "    }"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 230,
   "id": "ecb890ec",
   "metadata": {},
   "outputs": [],
   "source": [
    "with open(os.path.join(DATA_BASE_DIR, \"consolidate_label_project_info.json\"), \"w\") as f:\n",
    "    json.dump(save_data, f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b51ce8ca",
   "metadata": {},
   "outputs": [],
   "source": [
    "# delete a project\n",
    "# api.delete_work_item_set(\"89fb359f-6868-4f9e-9365-8c5c1b389df9\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 352,
   "id": "f9257cdb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2796"
      ]
     },
     "execution_count": 352,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# from suno_utils.labeler.client import Project\n",
    "results = []\n",
    "\n",
    "p = Project(\"fd6c8c75-2ffa-4af2-9b47-76f8246f4662\", \"vox_clean\", api)\n",
    "results += [e for e in p.list_data(limit=1000) if len(e[\"results\"]) > 0 and e[\"results\"]]\n",
    "\n",
    "p = Project(\"54103eec-4d47-4b5e-b78d-80a55236215b\", \"vox_other\", api)\n",
    "results += [e for e in p.list_data(limit=1000) if len(e[\"results\"]) > 0 and e[\"results\"]]\n",
    "\n",
    "p = Project(\"f14733ca-6de6-4896-a0c9-394f6e020ab3\", \"spgi_clean\", api)\n",
    "results += [e for e in p.list_data(limit=1000) if len(e[\"results\"]) > 0 and e[\"results\"]]\n",
    "\n",
    "p = Project(\"68b4718e-fb8b-45e6-8e13-41ac868e7f5e\", \"spgi_other\", api)\n",
    "results += [e for e in p.list_data(limit=1000) if len(e[\"results\"]) > 0 and e[\"results\"]]\n",
    "\n",
    "p = Project(\"79db1d18-6fc2-4538-97f0-8a1ecccbc4a2\", \"earnings22_clean\", api)\n",
    "results += [e for e in p.list_data(limit=1000) if len(e[\"results\"]) > 0 and e[\"results\"]]\n",
    "\n",
    "p = Project(\"61d9b503-972e-4d34-bf21-df9ae62b9d0f\", \"earnings22_other\", api)\n",
    "results += [e for e in p.list_data(limit=1000) if len(e[\"results\"]) > 0 and e[\"results\"]]\n",
    "\n",
    "p = Project(\"3910170c-07fb-4356-95ff-39d145c3338f\", \"libri_clean\", api)\n",
    "results += [e for e in p.list_data(limit=1000) if len(e[\"results\"]) > 0 and e[\"results\"]]\n",
    "\n",
    "p = Project(\"397f3abd-e0d6-4ade-bf3d-1b5afd217537\", \"libri_other\", api)\n",
    "results += [e for e in p.list_data(limit=1000) if len(e[\"results\"]) > 0 and e[\"results\"]]\n",
    "\n",
    "p = Project(\"377ee919-6112-4eea-89f8-5403a1e41363\", \"cv9_clean\", api)\n",
    "results += [e for e in p.list_data(limit=1000) if len(e[\"results\"]) > 0 and e[\"results\"]]\n",
    "\n",
    "p = Project(\"da38d8bc-1519-476a-a9ae-496ab001f4ca\", \"cv9_other\", api)\n",
    "results += [e for e in p.list_data(limit=1000) if len(e[\"results\"]) > 0 and e[\"results\"]]\n",
    "\n",
    "p = Project(\"fedefc37-fe2b-4918-9ee1-e2491a4a0f8f\", \"giga_clean\", api)\n",
    "results += [e for e in p.list_data(limit=1000) if len(e[\"results\"]) > 0 and e[\"results\"]]\n",
    "\n",
    "p = Project(\"8ce1c271-3019-43f8-9791-9c58566a130a\", \"giga_other\", api)\n",
    "results += [e for e in p.list_data(limit=1000) if len(e[\"results\"]) > 0 and e[\"results\"]]\n",
    "\n",
    "p = Project(\"a4cb789e-1637-494d-afdb-c1eb19d1789f\", \"ted_clean\", api)\n",
    "results += [e for e in p.list_data(limit=1000) if len(e[\"results\"]) > 0 and e[\"results\"]]\n",
    "\n",
    "p = Project(\"3bbe64f6-a739-4615-b72d-74067170bcdd\", \"ted_other\", api)\n",
    "results += [e for e in p.list_data(limit=1000) if len(e[\"results\"]) > 0 and e[\"results\"]]\n",
    "\n",
    "p = Project(\"6fcc478f-6f5c-4835-953e-98eaf817d5cc\", \"ami_clean\", api)\n",
    "results += [e for e in p.list_data(limit=1000) if len(e[\"results\"]) > 0 and e[\"results\"]]\n",
    "\n",
    "p = Project(\"3bb8b7b8-0f8d-4ff9-a171-97542e18a14d\", \"ami_other\", api)\n",
    "results += [e for e in p.list_data(limit=1000) if len(e[\"results\"]) > 0 and e[\"results\"]]\n",
    "\n",
    "len(results)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 353,
   "id": "4da9a5fa",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 2796 (vox, spgi, earnings22, libri, cv9, giga, ted, smi)\n",
    "with open(\"hand_labels.json\", \"w\") as f:\n",
    "    json.dump(results, f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "79aa4deb",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5e6013b7",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "249dcd97",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "3c3f834a",
   "metadata": {},
   "source": [
    "## Prep HF dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 444,
   "id": "15e9fdc2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2911\n"
     ]
    }
   ],
   "source": [
    "hand_annotations = {}\n",
    "\n",
    "with open(\"ami_hand_labels.json\") as f:\n",
    "    ami_hand_annotations = json.load(f)\n",
    "    \n",
    "for k, v in ami_hand_annotations.items():\n",
    "    hand_annotations[k] = v\n",
    "    \n",
    "with open(\"hand_labels.json\") as f:\n",
    "    hand_annotation_results = json.load(f)\n",
    "    \n",
    "for e in hand_annotation_results:\n",
    "    hand_annotations[e[\"externalId\"]] = e[\"results\"][0][\"data\"][\"text\"]\n",
    "    \n",
    "print(len(hand_annotations))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 445,
   "id": "4aa8e87d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2911 correct labels\n"
     ]
    }
   ],
   "source": [
    "segments_df = pd.read_csv(os.path.join(DATA_BASE_DIR, \"rev_annotated_samples.csv\"))\n",
    "segments_df = segments_df.fillna(\"\")\n",
    "segments_df[\"final_text\"] = segments_df[\"uid\"].map(hand_annotations)\n",
    "\n",
    "print((~segments_df[\"final_text\"].isnull()).sum(), \"correct labels\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 447,
   "id": "e1598d3b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "5449 correct labels\n"
     ]
    }
   ],
   "source": [
    "def _setify(s):\n",
    "    s = re.sub(r\"\\[.+?\\]\", \" \", s.lower())\n",
    "    s = re.sub(r\"[^a-z0-9\\']\", \" \", s.lower())\n",
    "    s = normalize_whitespace(s)\n",
    "    return set(s.split())\n",
    "\n",
    "# allows addition of words (um, uh etc)\n",
    "match_idx_mask = ((segments_df[\"text\"].apply(_setify) - segments_df[\"rev_text\"].apply(_setify)).str.len() == 0)\n",
    "segments_df.loc[match_idx_mask, \"final_text\"] = segments_df.loc[match_idx_mask, \"rev_text\"]\n",
    "print((~segments_df[\"final_text\"].isnull()).sum(), \"correct labels\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 448,
   "id": "868c3be6",
   "metadata": {},
   "outputs": [],
   "source": [
    "filtered_segments_df = segments_df.copy().dropna(subset=[\"final_text\"])\n",
    "# remove trailing hesitations\n",
    "filtered_segments_df[\"final_text\"] = filtered_segments_df[\"final_text\"].str.strip(\"- \")\n",
    "# remove metatags [singing] and [laughter]\n",
    "filtered_segments_df[\"final_text\"] = filtered_segments_df[\"final_text\"].apply(\n",
    "    lambda x: normalize_whitespace(re.sub(r\"\\[laughter|singing\\]\", \" \", x))\n",
    ")\n",
    "# filter out segments with other metatags (inaudible, foreign_language)\n",
    "filtered_segments_df = filtered_segments_df[~filtered_segments_df[\"final_text\"].str.contains(\"[\", regex=False)]\n",
    "filtered_segments_df[\"final_text\"] = filtered_segments_df[\"final_text\"].apply(normalize_whitespace)\n",
    "filtered_segments_df = filtered_segments_df[filtered_segments_df[\"final_text\"].str.len() > 0]\n",
    "filtered_segments_df = filtered_segments_df.reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 376,
   "id": "cced6370",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ami_clean: 32.8 mins to annotate\n",
      "ami_other: 32.8 mins to annotate\n",
      "cv9_clean: 34.8 mins to annotate\n",
      "cv9_other: 34.7 mins to annotate\n",
      "earnings22_clean: 35.1 mins to annotate\n",
      "earnings22_other: 34.2 mins to annotate\n",
      "giga_clean: 32.5 mins to annotate\n",
      "giga_other: 33.3 mins to annotate\n",
      "libri_clean: 35.1 mins to annotate\n",
      "libri_other: 35.2 mins to annotate\n",
      "spgi_clean: 35.0 mins to annotate\n",
      "spgi_other: 35.1 mins to annotate\n",
      "ted_clean: 32.7 mins to annotate\n",
      "ted_other: 33.3 mins to annotate\n",
      "vox_clean: 35.1 mins to annotate\n",
      "vox_other: 33.8 mins to annotate\n"
     ]
    }
   ],
   "source": [
    "for group_tag in sorted(set(filtered_segments_df[\"group_tag\"])):\n",
    "    df = filtered_segments_df[filtered_segments_df[\"group_tag\"] == group_tag]\n",
    "    n0 = round(df[\"duration_s\"].sum() / 60, 1)\n",
    "    print(\"{}: {} mins to annotate\".format(group_tag, n0))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 377,
   "id": "8f9aeab3",
   "metadata": {},
   "outputs": [],
   "source": [
    "# map back to original ID\n",
    "with open(os.path.join(DATA_BASE_DIR, \"raw_metadata.json\")) as f:\n",
    "    raw_metadata = json.load(f)\n",
    "uid_to_id = {\n",
    "    m[\"uid\"]: m[\"id\"] for m in raw_metadata\n",
    "}\n",
    "filtered_segments_df[\"original_id\"] = filtered_segments_df[\"uid\"].map(uid_to_id)\n",
    "assert(filtered_segments_df.isnull().sum().sum() == 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 381,
   "id": "80eba65f",
   "metadata": {},
   "outputs": [],
   "source": [
    "filtered_segments_df.to_csv(os.path.join(DATA_BASE_DIR, \"output_orthographic.csv\"), index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0a9e285c",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "e361a79d",
   "metadata": {},
   "source": [
    "## Normalize"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 538,
   "id": "b7a1ea1b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(5241, 15)"
      ]
     },
     "execution_count": 538,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "segments_df = pd.read_csv(os.path.join(DATA_BASE_DIR, \"output_orthographic.csv\"))\n",
    "segments_df = segments_df.fillna(\"\")\n",
    "segments_df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 384,
   "id": "ec27e1d2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[NeMo I 2022-09-26 08:11:30 post_processing:50] Post processing graph was restored from /tmp/prod_nemo_fst_georg/en_tn_post_processing.far.\n",
      "[NeMo I 2022-09-26 08:11:38 tokenize_and_classify_with_audio:99] ClassifyFst.fst was restored from /tmp/prod_nemo_fst_georg/_cased_en_tn_False_deterministicnemo_custom_norm.tsv.far.\n",
      "[NeMo I 2022-09-26 08:11:38 verbalize_final:52] VerbalizeFinalFst graph was restored from /tmp/prod_nemo_fst_georg/en_tn_False_deterministic_verbalizer.far.\n",
      "[NeMo I 2022-09-26 08:11:38 post_processing:50] Post processing graph was restored from /tmp/prod_nemo_fst_2_georg/en_tn_post_processing.far.\n",
      "[NeMo I 2022-09-26 08:11:38 tokenize_and_classify:85] ClassifyFst.fst was restored from /tmp/prod_nemo_fst_2_georg/en_tn_True_deterministic_cased_nemo_custom_norm.tsv_tokenize.far.\n",
      "[NeMo I 2022-09-26 08:11:38 verbalize_final:52] VerbalizeFinalFst graph was restored from /tmp/prod_nemo_fst_2_georg/en_tn_True_deterministic_verbalizer.far.\n"
     ]
    }
   ],
   "source": [
    "from suno_utils.utils.text_normalizer import normalize_mp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 400,
   "id": "755763dd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3.0 minutes runtime\n"
     ]
    }
   ],
   "source": [
    "t0 = time.time()\n",
    "norm_texts = normalize_mp(\n",
    "    [Tokens.from_text(s) for s in segments_df[\"final_text\"].tolist()],\n",
    "    segments_df[\"asr\"].tolist(),\n",
    ")\n",
    "t1 = time.time()\n",
    "print(round((t1 - t0) / 60, 1), \"minutes runtime\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 401,
   "id": "1ea34604",
   "metadata": {},
   "outputs": [],
   "source": [
    "segments_df[\"final_text_norm\"] = [t.text for t in norm_texts]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 402,
   "id": "1afb98b2",
   "metadata": {},
   "outputs": [],
   "source": [
    "segments_df.to_csv(os.path.join(DATA_BASE_DIR, \"output_norm.csv\"), index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c12f887f",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "1df4159b",
   "metadata": {},
   "source": [
    "## fix potential norm mistakes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3817333b",
   "metadata": {},
   "outputs": [],
   "source": [
    "# TODO: fix all the below (including transliterate unicode!!!)\n",
    "# TODO: scoring can be messed up cause of overall length preference\n",
    "\n",
    "# ## norm: \n",
    "# 1x, q3, \n",
    "# KRW - Korean Yuan\n",
    "# 16.5% - sixteen and a half percent\n",
    "# $4 to $5 - four to five dolla\n",
    "# 125,000 to 130,000 - one hundred and twenty five to one hundred and thirty thousand\n",
    "# * 1 - star one\n",
    "# March 22nd, 2021\n",
    "# i.e. -> i e\n",
    "# CET1 -> c e t one\n",
    "# 0.2% -> point two percent\n",
    "# 2 20 0 -> two twenty zero\n",
    "# 3 to $5 billion fine\n",
    "# 14.99 -> fourteen ninety nine\n",
    "# 5:00. -> five\n",
    "\n",
    "# St. -> saint\n",
    "# According to allmusic.com. -> dot com\n",
    "# .com/cook, to get\n",
    "# Switchboard or switchboard.live. \n",
    "# /maron/\n",
    "# IEEE - i triple e\n",
    "# AA - double a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 534,
   "id": "7a10c0ac",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "5241\n",
      "681\n"
     ]
    }
   ],
   "source": [
    "print(segments_df.shape[0])\n",
    "print(segments_df[\"final_text\"].str.contains(r\"[0-9]|[A-Z]{2,}|\\/|[^\\s]\\.[^\\s]\").sum())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 434,
   "id": "86ec235c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(681, 16)"
      ]
     },
     "execution_count": 434,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "norm_to_annotate_df = segments_df[\n",
    "    segments_df[\"final_text\"].str.contains(r\"[0-9]|[A-Z]{2,}|\\/|[^\\s]\\.[^\\s]\")\n",
    "]\n",
    "norm_to_annotate_df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 439,
   "id": "1815a30f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Um, and come up with some new ones for the next meeting, which will be in another 30 minutes.',\n",
       "       'um and come up with some new ones for the next meeting which will be in another thirty minutes'],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 439,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "norm_to_annotate_df.iloc[0][[\"final_text\", \"final_text_norm\"]].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 432,
   "id": "6ba74757",
   "metadata": {},
   "outputs": [],
   "source": [
    "from suno_utils.labeler.client import SunoAPIClient"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 433,
   "id": "20281245",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Token here https://datasets.suno.ai/console/settings\n",
    "api = SunoAPIClient(api_url='https://datasets-api.suno.ai/graphql/', token='bd60a8ce56e0407085bd7c59b774c4d0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 436,
   "id": "1f2d7766",
   "metadata": {},
   "outputs": [],
   "source": [
    "task_config_meta = {\n",
    "    \"blocks\": [\n",
    "        {\"data\": {\"key\": \"url\"}, \"type\": \"audio\", \"props\": {\"complex\": True}},\n",
    "        {\"data\": {\"key\": \"text\"}, \"type\": \"markdown\"},\n",
    "        {\"data\": {\"key\": \"text_norm\"}, \"type\": \"textarea\", \"props\": {\"placeholder\": \"\"}}, \n",
    "    ]\n",
    "}\n",
    "\n",
    "p = api.create_project(name=\"hf_norm_fixup\")\n",
    "\n",
    "datums = []\n",
    "for _, row in norm_to_annotate_df.iterrows():\n",
    "    datums.append({\n",
    "        \"metadata\": {\n",
    "            \"type\": \"audio\",\n",
    "            \"text_norm\": row[\"final_text_norm\"],\n",
    "#                 \"text_norm\": row[\"text_norm\"],\n",
    "            \"text\": row[\"final_text\"],\n",
    "#                 \"rev_text_norm\": row[\"rev_text_norm\"],\n",
    "        },\n",
    "        \"externalId\": row[\"uid\"],\n",
    "        \"storageKey\": f\"studio/projects/{PROJECT_ID}/{row['uid']}.wav\"\n",
    "    })\n",
    "datums_out = p.add_data(datums)\n",
    "\n",
    "# Once created, you can go https://console.suno.ai/ and click on the project and start labeling.\n",
    "task_out = p.add_task_config({'name': 'HF norm fixup', 'metadata': task_config_meta})\n",
    "\n",
    "save_data = {\n",
    "    \"project_id\": p.id,\n",
    "    \"task_id\": task_out[\"id\"],\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 437,
   "id": "df2c0d85",
   "metadata": {},
   "outputs": [],
   "source": [
    "with open(os.path.join(DATA_BASE_DIR, \"norm_label_project_info.json\"), \"w\") as f:\n",
    "    json.dump(save_data, f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 496,
   "id": "f9fbeb9d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "681"
      ]
     },
     "execution_count": 496,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# from suno_utils.labeler.client import Project\n",
    "p = Project(\"5a646472-763c-4fd3-b150-15802c309323\", \"hf_norm_fixup\", api)\n",
    "norm_results = [e for e in p.list_data(limit=1000) if len(e[\"results\"]) > 0 and e[\"results\"]]\n",
    "\n",
    "len(norm_results)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 498,
   "id": "787aed29",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 681\n",
    "with open(\"norm_hand_labels.json\", \"w\") as f:\n",
    "    json.dump(norm_results, f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f985d8bd",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2297099e",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6f76d4a9",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "39fff05a",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0155f9ba",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "9f2300b9",
   "metadata": {},
   "source": [
    "## Make distribution file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 834,
   "id": "eec28e39",
   "metadata": {},
   "outputs": [],
   "source": [
    "# TODO: comma before 'and' 'or' (oxford?)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 835,
   "id": "10dbf0d3",
   "metadata": {},
   "outputs": [],
   "source": [
    "segments_df = pd.read_csv(os.path.join(DATA_BASE_DIR, \"output_norm.csv\"))\n",
    "segments_df = segments_df.fillna(\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 836,
   "id": "2d7af55b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "681\n"
     ]
    }
   ],
   "source": [
    "with open(\"norm_hand_labels.json\") as f:\n",
    "    norm_results = json.load(f)\n",
    "    \n",
    "hand_annotations = {}\n",
    "for e in norm_results:\n",
    "    hand_annotations[e[\"externalId\"]] = e[\"results\"][0][\"data\"][\"text_norm\"]\n",
    "    \n",
    "print(len(hand_annotations))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 837,
   "id": "5a4ab91e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# overwrite hand-labeled\n",
    "segments_df[\"h\"] = segments_df[\"final_text_norm\"]\n",
    "segments_df[\"final_text_norm\"] = segments_df[\"uid\"].map(hand_annotations)\n",
    "segments_df[\"final_text_norm\"] = segments_df[\"final_text_norm\"].fillna(segments_df[\"h\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 838,
   "id": "d8cc81e9",
   "metadata": {},
   "outputs": [],
   "source": [
    "# some final fixes\n",
    "\n",
    "# remove unicode\n",
    "unicode_mask = segments_df[\"final_text\"].str.replace(\"\", \" \").apply(lambda x: max([ord(s) for s in x])) > 128\n",
    "segments_df = segments_df[~unicode_mask]\n",
    "\n",
    "# hesitations\n",
    "segments_df[\"final_text_norm\"] = segments_df[\"final_text_norm\"].apply(\n",
    "    lambda x: normalize_whitespace(x.replace(\"--\", \" \"))\n",
    ")\n",
    "\n",
    "# collapse hesitations\n",
    "segments_df[\"final_text\"] = segments_df[\"final_text\"].replace(r\"\\b[Ee]h\\b\", \"uh\", regex=True)\n",
    "segments_df[\"final_text_norm\"] = segments_df[\"final_text_norm\"].replace(r\"\\beh\\b\", \"uh\", regex=True)\n",
    "\n",
    "# fix dangling things\n",
    "from nltk.corpus import words as nltk_words\n",
    "COMMON_EN_WORDS = set(nltk_words.words())\n",
    "COMMON_EN_WORDS_LOWER = set([s.lower() for s in COMMON_EN_WORDS])\n",
    "def _fix_dangling(m, is_lower=False):\n",
    "    word_set = COMMON_EN_WORDS_LOWER if is_lower else COMMON_EN_WORDS\n",
    "    text = m.group()\n",
    "    word = text.strip(\" -\")\n",
    "    probably_fragment = word not in word_set\n",
    "    if probably_fragment:\n",
    "        return text\n",
    "    else:\n",
    "        return word\n",
    "def fix_dangling(s):\n",
    "    return re.sub(r\"[^\\s]+\\s\\-\\-$\", _fix_dangling, s)\n",
    "segments_df[\"final_text\"] = segments_df[\"final_text\"].apply(fix_dangling)\n",
    "segments_df[\"final_text\"] = segments_df[\"final_text\"].str.strip(\",\")\n",
    "\n",
    "# consolidate comma over hesitation\n",
    "def _fix_hesitation(m, is_lower=False):\n",
    "    word_set = COMMON_EN_WORDS_LOWER if is_lower else COMMON_EN_WORDS\n",
    "    text = m.group()\n",
    "    w0, w1 = text.split(\"--\")\n",
    "    w0 = w0.strip()\n",
    "    w1 = w1.strip()\n",
    "    probably_not_fragment = w0 in word_set\n",
    "    if w0 == w1 and probably_not_fragment:\n",
    "        return w0 + \", \" + w1\n",
    "    else:\n",
    "        return text\n",
    "def fix_hesitation(s):\n",
    "    return re.sub(r\"[^\\s]+\\s\\-\\-\\s[^\\s]+\", _fix_hesitation, s)\n",
    "segments_df[\"final_text\"] = segments_df[\"final_text\"].apply(fix_hesitation)\n",
    "\n",
    "# known abbreviations\n",
    "repl_patterns = [\n",
    "    (\"Dr.\", r\"\\bdr\\b\", \"doctor\"),\n",
    "    (\"Mr.\", r\"\\bmr\\b\", \"mister\"),\n",
    "    (\"Ms.\", r\"\\bms\\b\", \"miss\"),\n",
    "    (\"Mrs.\", r\"\\bmrs\\b\", \"misses\"),\n",
    "    (\"Sr.\", r\"\\bsr\\b\", \"senior\"),\n",
    "    (\"St.\", r\"\\bst\\b\", \"saint\"),\n",
    "]\n",
    "for e in repl_patterns:\n",
    "    mask = segments_df[\"final_text\"].str.contains(e[0], regex=False)\n",
    "    segments_df.loc[mask, \"final_text_norm\"] = segments_df.loc[\n",
    "        mask, \"final_text_norm\"\n",
    "    ].replace(e[1], e[2], regex=True)\n",
    "\n",
    "# somehow brakets made it through\n",
    "segments_df[\"final_text\"] = segments_df[\"final_text\"].replace(r\"\\s*[\\[\\]]\\s*\", \" \", regex=True)\n",
    "segments_df[\"final_text_norm\"] = segments_df[\"final_text_norm\"].replace(r\"\\s*[\\[\\]]\\s*\", \" \", regex=True)\n",
    "\n",
    "# remove useless quotes\n",
    "useless_quotes_mask = (\n",
    "    (segments_df[\"final_text\"].str[0] == \"\\\"\") &\n",
    "    (segments_df[\"final_text\"].str[-1] == \"\\\"\") &\n",
    "    (segments_df[\"final_text\"].str.count(\"\\\"\") == 2)\n",
    ")\n",
    "segments_df.loc[useless_quotes_mask, \"final_text\"] = segments_df.loc[\n",
    "    useless_quotes_mask, \"final_text\"\n",
    "].str.strip(\"\\\"\")\n",
    "\n",
    "# normalize whitespace and remove empties\n",
    "segments_df[\"final_text\"] = segments_df[\"final_text\"].apply(normalize_whitespace)\n",
    "segments_df[\"final_text_norm\"] = segments_df[\"final_text_norm\"].apply(normalize_whitespace)\n",
    "segments_df = segments_df[\n",
    "    (segments_df[\"final_text\"].str.len() > 0) &\n",
    "    (segments_df[\"final_text_norm\"].str.len() > 0)\n",
    "]\n",
    "\n",
    "excluded_uids = set([\n",
    "    '69aec86f-7470-46bb-a8df-27228e3e4277',\n",
    "    '910a8feb-492c-4a4b-aac3-3be5dc97bd0c',\n",
    "    '182266c7-1ef7-4338-9c68-793436ee6d3e',\n",
    "    'b36610f1-2565-45c0-a1b5-f6cdb0a48410',\n",
    "    'b51a44d3-b06c-48cc-80af-06cf7a70851c',\n",
    "    'f64fdbdf-45dd-42ed-83f6-117393e11a36',\n",
    "    '35d4128f-0d08-4736-94ed-da8381023397',\n",
    "    '24f8684f-84e9-417f-883b-d8b68e1d23af',\n",
    "    '282a67a6-8abf-4136-bfdb-dcd8f663207f',\n",
    "    'dfc836ce-07bd-4da9-a69b-43bc895e6a8e',\n",
    "    'eda2582d-fd31-4043-bdf1-6dbcea95a621',\n",
    "    '1907d088-497f-4b67-b281-ed0bc641f1ae',\n",
    "    \n",
    "    # consolidate hmm mm huh\n",
    "    \"f388a07e-4309-4bbd-9fa5-7359c86d0b64\",\n",
    "    \"478992e8-663a-4e0a-ba5d-36aa3fecd037\",\n",
    "    \"d57cc96b-15e4-4e40-a760-7504c239e6be\",\n",
    "    \"2474d3ee-d863-47cf-b0f0-facce9893895\",\n",
    "    \"2e2dc26d-a971-425d-b955-5db0791a370a\",\n",
    "    \"cdfbed92-2038-44c0-8946-2435d352b207\",\n",
    "    \"c6ac27a7-f736-4842-82b7-a8472fbf01ed\",\n",
    "    \"53d62313-c443-44ea-9731-4004587eeba8\",\n",
    "    \"ec92a53b-b9b0-40c3-a4fa-44e87f38a319\",\n",
    "    \"ebab24be-b240-4ec2-be93-686b456356e8\",\n",
    "    \"70052cfc-7fc2-4cae-918c-bf00478547ef\",\n",
    "    \"1d490c58-c143-4696-b1c8-680a26bf92a8\",\n",
    "    \"fe2889ee-3e88-4413-aff5-0b4659841580\",\n",
    "    \"372b053d-bbda-415e-b8ea-7e27acf6e475\",\n",
    "])\n",
    "\n",
    "segments_df = segments_df[~segments_df[\"uid\"].isin(excluded_uids)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 839,
   "id": "bce6973c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# make distribution\n",
    "distribute_df = segments_df[[\"group_tag\", \"uid\", \"original_id\", \"final_text\", \"final_text_norm\", \"duration_s\", \"uri\"]].copy()\n",
    "distribute_df = distribute_df.rename(columns={\"final_text\": \"transcript\", \"final_text_norm\": \"transcript_norm\"})\n",
    "distribute_df = distribute_df.reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 840,
   "id": "63f8208a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ami_clean: 32.0 mins to annotate\n",
      "ami_other: 32.5 mins to annotate\n",
      "cv9_clean: 34.8 mins to annotate\n",
      "cv9_other: 34.2 mins to annotate\n",
      "earnings22_clean: 34.7 mins to annotate\n",
      "earnings22_other: 34.0 mins to annotate\n",
      "giga_clean: 32.4 mins to annotate\n",
      "giga_other: 33.3 mins to annotate\n",
      "libri_clean: 35.1 mins to annotate\n",
      "libri_other: 35.2 mins to annotate\n",
      "spgi_clean: 35.0 mins to annotate\n",
      "spgi_other: 35.1 mins to annotate\n",
      "ted_clean: 32.0 mins to annotate\n",
      "ted_other: 32.1 mins to annotate\n",
      "vox_clean: 35.1 mins to annotate\n",
      "vox_other: 33.8 mins to annotate\n"
     ]
    }
   ],
   "source": [
    "for group_tag in sorted(set(distribute_df[\"group_tag\"])):\n",
    "    df = distribute_df[distribute_df[\"group_tag\"] == group_tag]\n",
    "    n0 = round(df[\"duration_s\"].sum() / 60, 1)\n",
    "    print(\"{}: {} mins to annotate\".format(group_tag, n0))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 841,
   "id": "7d947158",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "5187 samples\n"
     ]
    }
   ],
   "source": [
    "import string\n",
    "assert(len(set(\"\".join(public_distribute_df[\"transcript_norm\"])) - set(string.ascii_lowercase + \" '\")) == 0)\n",
    "print(distribute_df.shape[0], \"samples\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 842,
   "id": "fc0e0800",
   "metadata": {},
   "outputs": [],
   "source": [
    "distribute_df.to_json(\"internal_suno_set.jsonl\", lines=True, orient=\"records\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 846,
   "id": "847a509e",
   "metadata": {},
   "outputs": [],
   "source": [
    "public_distribute_df = distribute_df.drop([\"duration_s\", \"uid\", \"uri\"], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 847,
   "id": "3b91e3e2",
   "metadata": {},
   "outputs": [],
   "source": [
    "public_distribute_df.to_json(\"suno_set.jsonl\", lines=True, orient=\"records\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 848,
   "id": "81b7a534",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{\"group_tag\":\"ami_other\",\"original_id\":\"AMI_ES2011a_H00_FEE041_0005020_0005133\",\"transcript\":\"There we go.\",\"transcript_norm\":\"there we go\"}\r\n",
      "{\"group_tag\":\"ami_clean\",\"original_id\":\"AMI_ES2011a_H00_FEE041_0017316_0017402\",\"transcript\":\"Yeah.\",\"transcript_norm\":\"yeah\"}\r\n"
     ]
    }
   ],
   "source": [
    "!head -2 suno_set.jsonl"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7dfccb04",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1e625eaf",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "83f5a2ce",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2c476486",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "43124138",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "95724f63",
   "metadata": {},
   "source": [
    "## Push to hub"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 858,
   "id": "5548ee98",
   "metadata": {},
   "outputs": [],
   "source": [
    "distribute_df = pd.read_json(\"internal_suno_set.jsonl\", lines=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 859,
   "id": "fae454da",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>group_tag</th>\n",
       "      <th>uid</th>\n",
       "      <th>original_id</th>\n",
       "      <th>transcript</th>\n",
       "      <th>transcript_norm</th>\n",
       "      <th>duration_s</th>\n",
       "      <th>uri</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ami_other</td>\n",
       "      <td>7d52b3b0-a467-4665-bd67-1adfa7107cb9</td>\n",
       "      <td>AMI_ES2011a_H00_FEE041_0005020_0005133</td>\n",
       "      <td>There we go.</td>\n",
       "      <td>there we go</td>\n",
       "      <td>1.13</td>\n",
       "      <td>/mnt/data-ssd-1/data/academia/hf_paper/ami/7d5...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ami_clean</td>\n",
       "      <td>c809f93c-df43-47b2-b615-978bc9e0bb9a</td>\n",
       "      <td>AMI_ES2011a_H00_FEE041_0017316_0017402</td>\n",
       "      <td>Yeah.</td>\n",
       "      <td>yeah</td>\n",
       "      <td>0.86</td>\n",
       "      <td>/mnt/data-ssd-1/data/academia/hf_paper/ami/c80...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   group_tag                                   uid  \\\n",
       "0  ami_other  7d52b3b0-a467-4665-bd67-1adfa7107cb9   \n",
       "1  ami_clean  c809f93c-df43-47b2-b615-978bc9e0bb9a   \n",
       "\n",
       "                              original_id    transcript transcript_norm  \\\n",
       "0  AMI_ES2011a_H00_FEE041_0005020_0005133  There we go.     there we go   \n",
       "1  AMI_ES2011a_H00_FEE041_0017316_0017402         Yeah.            yeah   \n",
       "\n",
       "   duration_s                                                uri  \n",
       "0        1.13  /mnt/data-ssd-1/data/academia/hf_paper/ami/7d5...  \n",
       "1        0.86  /mnt/data-ssd-1/data/academia/hf_paper/ami/c80...  "
      ]
     },
     "execution_count": 859,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "distribute_df.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "90df2996",
   "metadata": {},
   "outputs": [],
   "source": [
    "data = []\n",
    "for _, row in distribute_df.iterrows():\n",
    "    data.append({\n",
    "        \"id\": row[\"original_id\"],\n",
    "        \"norm_transcript\": row[\"transcript_norm\"],\n",
    "        \"ortho_transcript\": row[\"transcript\"],\n",
    "        \"group_tag\": row[\"group_tag\"],\n",
    "        \"audio\": [],\n",
    "        \"sampling_rate\": 16_000,\n",
    "    })"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 860,
   "id": "7650c83c",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 877,
   "id": "ff7c5746",
   "metadata": {},
   "outputs": [],
   "source": [
    "import json\n",
    "from datasets import Dataset, Audio\n",
    "\n",
    "hf_auth_token_write = \"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\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 884,
   "id": "80c63cd3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ami_clean\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "fefdf72b2b5346ebbe8b2b88b6add0a3",
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       "model_id": "f3dfa9c5649a42dc93ba6baca16c69a1",
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ami_other\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "4bf8027a51554adf910e920527366219",
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       "model_id": "e8578519fe1c4a1992ca8e09f86611ea",
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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       "model_id": "4a757584e50343d9a86c736e0c1887a1",
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      "text/plain": [
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Updating downloaded metadata with the new split.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "cv9_clean\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "5e12b3a5d92e467a8fede73665684de4",
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    },
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       "model_id": "3a11a6280a18416ba8b4bed510028f06",
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      ]
     },
     "metadata": {},
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    },
    {
     "data": {
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       "model_id": "c17002ebb9714ba38f0e808561a6d442",
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Updating downloaded metadata with the new split.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "cv9_other\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "c89641f1a9454139ae4a5178ae33b875",
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    },
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       "model_id": "3672371f3ab143dc9f28f4dfdfe0f193",
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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       "model_id": "844924534b74446794d7ace586688761",
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Updating downloaded metadata with the new split.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "earnings22_clean\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "ddfd32e264da48d08af3733b6d907866",
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      "earnings22_other\n"
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      "Updating downloaded metadata with the new split.\n"
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     "text": [
      "ted_other\n"
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      "Updating downloaded metadata with the new split.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "vox_clean\n"
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    {
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      "Updating downloaded metadata with the new split.\n"
     ]
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    {
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     "output_type": "stream",
     "text": [
      "vox_other\n"
     ]
    },
    {
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       "model_id": "42eea067340e4580bdd2baf5455e633d",
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    {
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       "model_id": "64a600fe17674c459cd7317c0eacbe4f",
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    },
    {
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       "model_id": "d117a300a5f848d68e67f348dee68d67",
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      },
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      ]
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    {
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   ],
   "source": [
    "for group_tag in sorted(set(distribute_df[\"group_tag\"])):\n",
    "    print(group_tag)\n",
    "    df = distribute_df[distribute_df[\"group_tag\"] == group_tag]\n",
    "    audio_dataset = Dataset.from_dict({\n",
    "        \"audio\": df[\"uri\"].tolist(),\n",
    "        \"ortho_transcript\": df[\"transcript\"].tolist(),\n",
    "        \"norm_transcript\": df[\"transcript_norm\"].tolist(),\n",
    "        \"id\": df[\"original_id\"].tolist(),\n",
    "#         \"group_tag\": distribute_df[\"group_tag\"].head(20).tolist(),\n",
    "    }).cast_column(\"audio\", Audio())\n",
    "    audio_dataset.push_to_hub(\"dan-oneill/test3_suno_resr\", split=group_tag, token=hf_auth_token_write)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 885,
   "id": "7b38006b",
   "metadata": {},
   "outputs": [],
   "source": [
    "# suno_test = load_dataset(\"dan-oneill/test1_suno_resr\", split=\"blabla\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "95ad64ff",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "204fa539",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 198,
   "id": "1971ee0e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# # remove mm other than mm hmm and remove hmm other than mm hmm\n",
    "# def _repl_mm(m):\n",
    "#     s = m.group(0)\n",
    "#     if s[-1] in set(string.ascii_lowercase) and s[-2] == \" \":\n",
    "#         return s[-1].upper() if s[0] == \"M\" else s[-1]\n",
    "#     return \"\"\n",
    "\n",
    "# def _fix_mm(s):\n",
    "#     return re.sub(r\"\\b([Mm]m[\\,\\.\\?\\s]*[a-z]?)(?!\\-)\", _repl_mm, s)\n",
    "\n",
    "# def _fix_mm_lower(s):\n",
    "#     return normalize_whitespace(re.sub(r\"\\b(mm)(?! hmm)\", \"\", s))\n",
    "\n",
    "# def _repl_hmm(m):\n",
    "#     s = m.group(0)\n",
    "#     if s[-1] in set(string.ascii_lowercase) and s[-2] == \" \":\n",
    "#         return s[-1].upper() if s[0] == \"M\" else s[-1]\n",
    "#     return \"\"\n",
    "\n",
    "# def _fix_hmm(s):\n",
    "#     return re.sub(r\"(?<![Mm]m\\-)\\b([Hh]mm[\\,\\.\\?\\s]*[a-z]?)\", _repl_hmm, s)\n",
    "\n",
    "# def _fix_hmm_lower(s):\n",
    "#     return normalize_whitespace(re.sub(r\"(?<!mm )\\b(hmm)\", \"\", s))\n",
    "\n",
    "# def _repl_huh(m):\n",
    "#     s = m.group(0)\n",
    "#     if s[-1] in set(string.ascii_lowercase) and s[-2] == \" \":\n",
    "#         return s[-1].upper() if s[0] == \"H\" else s[-1]\n",
    "#     return \"\"\n",
    "\n",
    "# def _fix_huh(s):\n",
    "#     return re.sub(r\"(?<![Uu]h\\-)\\b([Hh]uh[\\,\\.\\?\\s]*[a-z]?)\", _repl_huh, s)\n",
    "\n",
    "# def _fix_huh_lower(s):\n",
    "#     return normalize_whitespace(re.sub(r\"(?<!uh )(huh)\\b\", \"\", s))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 857,
   "id": "1f8367b1",
   "metadata": {},
   "outputs": [],
   "source": [
    "# print(_fix_mm(\"Mm. Yeah.\"))\n",
    "# print(_fix_mm(\"Mm, yeah.\"))\n",
    "# print(_fix_mm(\"mm, yeah.\"))\n",
    "\n",
    "# print(_fix_mm_lower(\"mm hmm\"))\n",
    "# print(_fix_mm_lower(\"mm and\"))\n",
    "# print(_fix_mm_lower(\"mm\"))\n",
    "\n",
    "# print(_fix_hmm(\"Mm-hmm.\"))\n",
    "# print(_fix_hmm(\"Hmm.\"))\n",
    "# print(_fix_hmm(\"Hmm, this\"))\n",
    "\n",
    "# print(_fix_hmm_lower(\"mm hmm\"))\n",
    "# print(_fix_hmm_lower(\"mm and\"))\n",
    "# print(_fix_hmm_lower(\"hmm\"))\n",
    "\n",
    "# print(_fix_huh(\"huh\"))\n",
    "# print(_fix_huh(\"Huh?\"))\n",
    "# print(_fix_huh(\"hkjasd, huh, as\"))\n",
    "# print(_fix_huh(\"and. Huh, as\"))\n",
    "# print(_fix_huh(\"Uh-huh\"))\n",
    "\n",
    "# print(_fix_huh_lower(\"huh\"))\n",
    "# print(_fix_huh_lower(\"huh as\"))\n",
    "# print(_fix_huh_lower(\"uh huh\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a2f48c1b",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c8cb2ea5",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "ba480a1d",
   "metadata": {},
   "source": [
    "## Local version"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "752ff9ef",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "\n",
    "import shutil\n",
    "import pandas as pd\n",
    "import tqdm\n",
    "\n",
    "from suno_utils.utils.text import write_jsonl\n",
    "\n",
    "SUNO_BASE_DIR = \"/mnt/data-ssd-1/data/academia/hf_paper/suno_dataset\"\n",
    "\n",
    "distribute_df = pd.read_json(\"internal_suno_set.jsonl\", lines=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "65db5c6b",
   "metadata": {},
   "outputs": [],
   "source": [
    "shutil.rmtree(SUNO_BASE_DIR, ignore_errors=True)\n",
    "os.makedirs(SUNO_BASE_DIR, exist_ok=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "88b7448f",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 5187/5187 [00:05<00:00, 877.62it/s]\n"
     ]
    }
   ],
   "source": [
    "metadata = []\n",
    "for _, row in tqdm.tqdm(distribute_df.iterrows(), total=distribute_df.shape[0]):\n",
    "    from_fp = row[\"uri\"]\n",
    "    to_fn = row[\"uid\"] + \".wav\"\n",
    "    rel_to_dir = os.path.join(\"audio\", row[\"group_tag\"])\n",
    "    to_dir = os.path.join(SUNO_BASE_DIR, rel_to_dir)\n",
    "    os.makedirs(to_dir, exist_ok=True)\n",
    "    rel_to_fp = os.path.join(rel_to_dir, to_fn)\n",
    "    to_fp = os.path.join(to_dir, to_fn)\n",
    "    shutil.copy(from_fp, to_fp)\n",
    "    metadata.append({\n",
    "        \"group_tag\": row[\"group_tag\"],\n",
    "        \"uid\": row[\"uid\"],\n",
    "        \"original_id\": row[\"original_id\"],\n",
    "        \"transcript\": row[\"transcript\"],\n",
    "        \"transcript_norm\": row[\"transcript_norm\"],\n",
    "        \"duration_s\": row[\"duration_s\"],\n",
    "        \"uri\": rel_to_fp,\n",
    "    })"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "b0dc8e6e",
   "metadata": {},
   "outputs": [],
   "source": [
    "write_jsonl(metadata, os.path.join(SUNO_BASE_DIR, \"manifest.jsonl\"))     "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "17c9bce0",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e99e5ec8",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b1329560",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "75e8902d",
   "metadata": {},
   "source": [
    "## (optional) final checks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 849,
   "id": "aa453d44",
   "metadata": {},
   "outputs": [],
   "source": [
    "l = list(range(distribute_df.shape[0]))\n",
    "random.seed(6006)\n",
    "random.shuffle(l)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 887,
   "id": "cf3bbb02",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "group_tag                                                  ami_other\n",
       "uid                             7d52b3b0-a467-4665-bd67-1adfa7107cb9\n",
       "original_id                   AMI_ES2011a_H00_FEE041_0005020_0005133\n",
       "transcript                                              There we go.\n",
       "transcript_norm                                          there we go\n",
       "duration_s                                                      1.13\n",
       "uri                /mnt/data-ssd-1/data/academia/hf_paper/ami/7d5...\n",
       "Name: 0, dtype: object"
      ]
     },
     "execution_count": 887,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "distribute_df.iloc[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "97b933f5",
   "metadata": {},
   "outputs": [],
   "source": [
    "n = 0\n",
    "for idx in l:\n",
    "    row = distribute_df.iloc[idx]\n",
    "    if not re.search(r\"[0-9]\", row[\"transcript\"]):\n",
    "        continue\n",
    "    Audio.from_file(row[\"uri\"]).play()\n",
    "    print(row[\"uid\"])\n",
    "    print(row[\"transcript\"])\n",
    "    print(row[\"transcript_norm\"])\n",
    "    print(\"-\"*10)\n",
    "    n += 1\n",
    "    if n == 10:\n",
    "        break"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "540c1d4c",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e7c8e8c2",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 896,
   "id": "9371470c",
   "metadata": {},
   "outputs": [],
   "source": [
    "segments_df = pd.read_csv(os.path.join(DATA_BASE_DIR, \"rev_annotated_samples.csv\"))\n",
    "raw_text_map = segments_df.set_index(\"uid\")[\"raw_text\"].to_dict()\n",
    "test_df = distribute_df.copy()\n",
    "test_df[\"raw_text\"] = test_df[\"uid\"].map(raw_text_map)\n",
    "test_df = test_df.fillna(\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 909,
   "id": "3a4d426c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(35, 8)"
      ]
     },
     "execution_count": 909,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = test_df[\n",
    "    (test_df[\"group_tag\"].str.contains(r\"libri\")) &\n",
    "    (test_df[\"transcript\"].str.contains(r\"\\\"\")) &\n",
    "#     (~test_df[\"raw_text\"].str.lower().str.contains(r\"\\buh\\b\"))\n",
    "]\n",
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 913,
   "id": "365fc39d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "group_tag                                                  ami_other\n",
       "uid                             7d52b3b0-a467-4665-bd67-1adfa7107cb9\n",
       "original_id                   AMI_ES2011a_H00_FEE041_0005020_0005133\n",
       "transcript                                              There we go.\n",
       "transcript_norm                                          there we go\n",
       "duration_s                                                      1.13\n",
       "uri                /mnt/data-ssd-1/data/academia/hf_paper/ami/7d5...\n",
       "raw_text                                                 THERE WE GO\n",
       "Name: 0, dtype: object"
      ]
     },
     "execution_count": 913,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_df.iloc[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 912,
   "id": "eae57c8a",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<audio controls=\"controls\" autobuffer=\"autobuffer\" style=\"\">\n",
       "  <source 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      "4448760-407\n",
      "And regarding, eh, long growth, just to, to, to repeat, eh, what, eh, I answered Sebastian at the beginning, we're looking into, eh, commercial lending growing somewhere in the six, eh, to 8% area and, eh, the consumer side, the retail side, growing more in the 12 to 14%, eh, area.\n",
      "And regarding, uh, long growth, just to, to, to repeat, uh, what, uh, I answered Sebastian at the beginning, uh, we're looking into, uh, commercial lending growing somewhere in the six, uh, to 8% area and, uh, the consumer side, the retail side, growing more in the 12 to 14%, uh\n",
      "and regarding uh long growth just to to to repeat uh what uh i answered sebastian at the beginning uh we're looking into uh commercial lending growing somewhere in the six uh to eight percent area and uh the consumer side the retail side growing more in the twelve to fourteen percent uh\n",
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\"/>\n",
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      "4461799-283\n",
      "So going through 2022, we'll still enjoy, um, a lower cost of regasification of the LNG that, that is delivered.\n",
      "So going through 2022, we'll still enjoy, um, a lower cost of regasification of the LNG that, that is delivered. Uh\n",
      "so going through twenty twenty two we'll still enjoy um a lower cost of regasification of the l n g that that is delivered uh\n",
      "----------\n"
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     "text": [
      "4461799-573\n",
      "Um, clearly our generation capacity comes down in Q4 as, and we get less sun.\n",
      "Um, clearly our generation capacity comes down in Q4 as, and we get less sun. Uh\n",
      "um clearly our generation capacity comes down in q four as and we get less sun uh\n",
      "----------\n"
     ]
    },
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\"/>\n",
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       "<IPython.core.display.HTML object>"
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     "metadata": {},
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "YOU1000000020_S0000242\n",
      "YOU KNOW MAGIC IS TWENTY YEARS OLD <COMMA> YOU KNOW MAGIC IS OLD ENOUGH THAT AH THERE ARE PEOPLE WHO PLAYED THE GAME WHEN THEY WERE YOUNGER WHO ARE SHARING IT WITH YOU KNOW THEIR YOUNGER GENERATIONS <PERIOD>\n",
      "You know, Magic is 20 years old, you know? Magic is old enough that, uh, there are people who played the game when they were younger who are sharing it with, you know, their younger generations.\n",
      "you know magic is twenty years old you know magic is old enough that uh there are people who played the game when they were younger who are sharing it with you know their younger generations\n",
      "----------\n"
     ]
    },
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\"/>\n",
       "  Your browser does not support the audio element.\n",
       "</audio>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "YOU1000000044_S0000985\n",
      "THIS IS THE <COMMA> THIS IS IT <COMMA> THIS IS WHAT I'VE BEEN USING SINCE TWENTY-SIXTEEN AND IT'S PROVEN TO BE A VERY GOOD CAMERA <PERIOD>\n",
      "This is, uh, this is it. This is what I've been using since 2016, and it's proven to be a very good camera.\n",
      "this is uh this is it this is what i've been using since twenty sixteen and it's proven to be a very good camera\n",
      "----------\n"
     ]
    },
    {
     "data": {
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     "text": [
      "POD1000000018_S0000287\n",
      "AH ELYRIA JORDAN BIOGRAPHY ON JIM REEVES HAD A BUNCH OF GREAT INFORMATION ON THE JIM DANDY OPRY SCANDAL <PERIOD> I FOUND A BILLBOARD MAGAZINE FROM NINETEEN FIFTY-SIX REPORTING THAT PHILIP MORRIS PAID OVER FOUR HUNDRED THOUSAND DOLLARS FOR THE TALENT ON THAT FIRST PACKAGE TOUR <PERIOD>\n",
      "Uh, Larry Jordan's biography on Jim Reeves had a bunch of great information on the Jim Denny Opry scandal. I found a Billboard magazine from 1956 reporting that Philip Morris paid over $400,000 for the talent on that first package tour.\n",
      "uh larry jordan's biography on jim reeves had a bunch of great information on the jim denny opry scandal i found a billboard magazine from nineteen fifty six reporting that philip morris paid over four hundred thousand dollars for the talent on that first package tour\n",
      "----------\n"
     ]
    },
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\"/>\n",
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       "</audio>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "YOU1000000000_S0000056\n",
      "AH IT'S SO AH CAPABLE YET DRIVES ALMOST LIKE A ALMOST LIKE A CAR AND IT HAS GREAT SOUND OF V EIGHT <PERIOD>\n",
      "Uh, it's so, uh, capable yet drives almost like a, almost like a car and it has great sound of V8.\n",
      "uh it's so uh capable yet drives almost like a almost like a car and it has great sound of v eight\n",
      "----------\n"
     ]
    },
    {
     "data": {
      "text/html": [
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\"/>\n",
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       "</audio>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "507d9b3ae737945d7c32fb038c00d766/156.wav\n",
      "In terms of the investigation, we filed our 10-K last night, and if you read the legal disclosure section, you'll see that there's really no change to the disclosure there,\n",
      "In terms of the investigation, we filed our 10-K last night, uh, and if you read the Legal Disclosure section, you'll see that there's really no change to the disclosure there.\n",
      "in terms of the investigation we filed our ten k last night uh and if you read the legal disclosure section you'll see that there's really no change to the disclosure there\n",
      "----------\n"
     ]
    },
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\"/>\n",
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      "2c96c94532cf532d609366011265d091/18.wav\n",
      "sort of a little out of the ordinary in Q1. But we had some really good activity on new customers.\n",
      "Sort of, uh, a little out of the ordinary in Q1, but, uh, we had some really good activity on, on new customers\n",
      "sort of uh a little out of the ordinary in q one but uh we had some really good activity on on new customers\n",
      "----------\n"
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\"/>\n",
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      "104cdd1abaa1ac00f81f892f73cd18bf/153.wav\n",
      "and these sites. We did do the investigations at sites that date all the way back to the late '70s and '80s. We have done most of the design work at a number of the facilities and these are everything from the large naval bases all up and down\n",
      "And these sites. We did do the investigations at sites that date all the way back to the late '70s and '80s. We have done most of the, uh, design work on a number of the facilities, and these are everything from the large naval bases all up and down\n",
      "and these sites we did do the investigations at sites that date all the way back to the late seventies and eighties we have done most of the uh design work on a number of the facilities and these are everything from the large naval bases all up and down\n",
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\"/>\n",
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       "</audio>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "887f2b31b093cbac639595e7fb5f82b2/44.wav\n",
      "Outside of Indiana and Ohio, we generally extend our portfolio to in-market developers who have a more national reach. And no state outside of Indiana and Ohio comprises more than 5% of the total construction book.\n",
      "Outside of Indiana and Ohio, we generally extend our portfolio to in-market developers who have a more, uh, national reach. And no state outside of Indiana and Ohio comprises more than 5% of the total construction book.\n",
      "outside of indiana and ohio we generally extend our portfolio to in market developers who have a more uh national reach and no state outside of indiana and ohio comprises more than five percent of the total construction book\n",
      "----------\n"
     ]
    },
    {
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\"/>\n",
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      "e9f74bbbfcf3a023347a07b622ce46e7/105.wav\n",
      "to a greater number of channels, 10, 15, 20. We chose not to do that at the time that it was occurring.\n",
      "To a greater number of channels, uh, 10, 15, 20. We chose not to do that at the time that it was occurring.\n",
      "to a greater number of channels uh ten fifteen twenty we chose not to do that at the time that it was occurring\n",
      "----------\n"
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      "1d1334c7d109585c1739f8580e50fe5a/148.wav\n",
      "We are extremely proud of the work that we've accomplished in the fourth quarter and full year 2018. We are pleased by the early momentum that we have in 2019. And we look forward to coming back in early May and sharing results\n",
      "We are extremely proud of the work we've accomplished in the fourth quarter and full year 2018. Uh, we're pleased by the early year momentum that we have in 2019, and we look forward to coming back in early May and sharing results\n",
      "we are extremely proud of the work we've accomplished in the fourth quarter and full year twenty eighteen uh we're pleased by the early year momentum that we have in twenty nineteen and we look forward to coming back in early may and sharing results\n",
      "----------\n"
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\"/>\n",
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      "Craig_Venter-53.74-68.57-<F0_M>\n",
      "paring it down to minimal components we 've been digitizing it now for almost twenty years when we sequenced the human genome it was going from the analog world of biology into the digital world of the computer\n",
      "Paring it down to minimal components. Uh, we've been digitizing it now for almost 20 years. When we sequenced the human genome. It was going from the analog world of biology into the digital world of the computer.\n",
      "paring it down to minimal components uh we've been digitizing it now for almost twenty years when we sequenced the human genome it was going from the analog world of biology into the digital world of the computer\n",
      "----------\n"
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\"/>\n",
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     "text": [
      "Craig_Venter-167.02-177.42-<F0_M>\n",
      "we started this over fifteen years ago it took several stages in fact starting with a bioethical review before we did the first experiments\n",
      "We started this, uh, over 15 years ago. It took several stages, in fact, starting with a bioethical review before we did the first experiments.\n",
      "we started this uh over fifteen years ago it took several stages in fact starting with a bioethical review before we did the first experiments\n",
      "----------\n"
     ]
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\"/>\n",
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     "text": [
      "Craig_Venter-177.42-189.16-<F0_M>\n",
      "but it turns out synthesizing dna is very difficult there 's tens of thousands of machines around the world that make small pieces of dna thirty to fifty letters in length\n",
      "But it turns out synthesizing DNA is very difficult. Uh, there's tens of thousands of machines around the world that make small pieces of DNA, uh, 30 to 50 letters in length.\n",
      "but it turns out synthesizing d n a is very difficult uh there's tens of thousands of machines around the world that make small pieces of d n a uh thirty to fifty letters in length\n",
      "----------\n"
     ]
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\"/>\n",
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      "Craig_Venter-307.79-327.39-<F0_M>\n",
      "we have to design so they can go together we design unique elements into this you may have read that we put watermarks in think of this we have a four letter genetic code a c g and t triplets of that letter of those letters code for roughly twenty amino acids that there 's a single letter\n",
      "Uh, we have to design so they can go together. We design unique elements into this. Uh, you may have read that we, uh, put watermarks in. Uh, think of this -- we have a four letter genetic code, A, C, G and T. Triplets of that letters of those letters code for roughly 20 amino acids, that there's a single letter\n",
      "uh we have to design so they can go together we design unique elements into this uh you may have read that we uh put watermarks in uh think of this we have a four letter genetic code a c g and t triplets of that letters of those letters code for roughly twenty amino acids that there's a single letter\n",
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      "Craig_Venter-341.67-356.97-<F0_M>\n",
      "we designed these pieces so we can just chew back with enzymes there 's enzymes that repair them and put them together and we started making pieces starting with pieces that were five to seven thousand seven thousand letters\n",
      "Uh, we designed these pieces so, uh, we can just chew back with enzymes. Uh, there's enzymes that repair them and put them together. And we started, uh, making pieces, starting with pieces that were five to seven thou -- uh, uh, 7,000 letters.\n",
      "uh we designed these pieces so uh we can just chew back with enzymes uh there's enzymes that repair them and put them together and we started uh making pieces starting with pieces that were five to seven thou uh uh seven thousand letters\n",
      "----------\n"
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\"/>\n",
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      "Craig_Venter-356.97-376.46-<F0_M>\n",
      "fit those together to make twenty four thousand letter pieces then put sets of those going up to seventy two thousand at each stage we grew up these pieces in abundance so we could sequence them because we 're trying to create a process that 's extremely robust that you can see in a minute we 're trying to get to the point of automation\n",
      "Fit those together to make 24,000 letter pieces, then put, uh, sets of those going up to 72,000. At each stage, we grew up these pieces in abundance so we could sequence them, because we're trying to create a process that's extremely, uh, robust, uh, that you can see in a minute. Uh, we're trying to get to the point of automation.\n",
      "fit those together to make twenty four thousand letter pieces then put uh sets of those going up to seventy two thousand at each stage we grew up these pieces in abundance so we could sequence them because we're trying to create a process that's extremely uh robust uh that you can see in a minute uh we're trying to get to the point of automation\n",
      "----------\n"
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\"/>\n",
       "  Your browser does not support the audio element.\n",
       "</audio>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Craig_Venter-415.08-427.36-<F0_M>\n",
      "twelve to twenty four hours later it put it back together exactly as it was before we have thousands of organisms that can do this these organisms can be totally desiccated they can live in a vacuum\n",
      "12 to 24 hours later, it put it back together exactly as it was before. Uh, we have thousands of organisms that can do this. These organisms can be totally desiccated, they can live in a vacuum.\n",
      "twelve to twenty four hours later it put it back together exactly as it was before uh we have thousands of organisms that can do this these organisms can be totally desiccated they can live in a vacuum\n",
      "----------\n"
     ]
    }
   ],
   "source": [
    "for i_, row in df.iloc[:20].iterrows():\n",
    "    Audio.from_file(row[\"uri\"]).play()\n",
    "    print(row[\"original_id\"])\n",
    "    print(row[\"raw_text\"])\n",
    "    print(row[\"transcript\"])\n",
    "    print(row[\"transcript_norm\"])\n",
    "    print(\"-\"*10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fe12ea35",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8f518244",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "29bbfce0",
   "metadata": {},
   "source": [
    "## Examples"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "430dc4f5",
   "metadata": {},
   "outputs": [],
   "source": [
    "829d44f9-5106-4073-8854-8638da2d47b3 - eye patch"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ad523841",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "96b17b4f",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "96bdd741",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "446fbf4b",
   "metadata": {},
   "source": [
    "## Label feedback"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1668c9a1",
   "metadata": {},
   "outputs": [],
   "source": [
    "speedup causes some missing audio, especially at the ed\n",
    "allow highlighting of spans in markdown (so that we can do diff visualization like here: https://www.diffchecker.com/)\n",
    "allow looping audio (maybe extra checkbox)\n",
    "audio should play immediately when seeking into waveform\n",
    "issues with seeking into waveform: plays from inconsistent spot\n",
    "spellcheck only shows when clicking into textbox\n",
    "spellcheck on markdown fields?\n",
    "back button\n",
    "\n",
    "'2001.' at beginning of markdown field gives weird offset\n",
    "shift enter submit\n",
    "hotkey (eg ctrl) to click on words\n",
    "volume normalization\n",
    "text input size gets large when placeeholder larger"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5217aede",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "15a972ef",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "38f18195",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "23c60480",
   "metadata": {},
   "source": [
    "## Turk task"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "id": "2d678cfd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>dataset</th>\n",
       "      <th>index</th>\n",
       "      <th>uid</th>\n",
       "      <th>uri</th>\n",
       "      <th>wer</th>\n",
       "      <th>raw_text</th>\n",
       "      <th>asr</th>\n",
       "      <th>text</th>\n",
       "      <th>text_norm</th>\n",
       "      <th>duration_s</th>\n",
       "      <th>group_tag</th>\n",
       "      <th>rev_text</th>\n",
       "      <th>rev_text_norm</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ami</td>\n",
       "      <td>6</td>\n",
       "      <td>7d52b3b0-a467-4665-bd67-1adfa7107cb9</td>\n",
       "      <td>/mnt/data-ssd-1/data/academia/hf_paper/ami/7d5...</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>THERE WE GO</td>\n",
       "      <td>there you go</td>\n",
       "      <td>There we go.</td>\n",
       "      <td>there we go</td>\n",
       "      <td>1.13</td>\n",
       "      <td>ami_other</td>\n",
       "      <td>There we go.</td>\n",
       "      <td>there we go</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ami</td>\n",
       "      <td>31</td>\n",
       "      <td>c809f93c-df43-47b2-b615-978bc9e0bb9a</td>\n",
       "      <td>/mnt/data-ssd-1/data/academia/hf_paper/ami/c80...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>YEAH</td>\n",
       "      <td>yeah</td>\n",
       "      <td>Yeah.</td>\n",
       "      <td>yeah</td>\n",
       "      <td>0.86</td>\n",
       "      <td>ami_clean</td>\n",
       "      <td>Yeah.</td>\n",
       "      <td>yeah</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  dataset  index                                   uid  \\\n",
       "0     ami      6  7d52b3b0-a467-4665-bd67-1adfa7107cb9   \n",
       "1     ami     31  c809f93c-df43-47b2-b615-978bc9e0bb9a   \n",
       "\n",
       "                                                 uri       wer     raw_text  \\\n",
       "0  /mnt/data-ssd-1/data/academia/hf_paper/ami/7d5...  0.333333  THERE WE GO   \n",
       "1  /mnt/data-ssd-1/data/academia/hf_paper/ami/c80...  0.000000         YEAH   \n",
       "\n",
       "            asr          text    text_norm  duration_s  group_tag  \\\n",
       "0  there you go  There we go.  there we go        1.13  ami_other   \n",
       "1          yeah         Yeah.         yeah        0.86  ami_clean   \n",
       "\n",
       "       rev_text rev_text_norm  \n",
       "0  There we go.   there we go  \n",
       "1         Yeah.          yeah  "
      ]
     },
     "execution_count": 168,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "segments_df = pd.read_csv(os.path.join(DATA_BASE_DIR, \"rev_annotated_samples.csv\"))\n",
    "segments_df = segments_df.fillna(\"\")\n",
    "segments_df.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 170,
   "id": "79c9ea73",
   "metadata": {},
   "outputs": [],
   "source": [
    "task_config_meta = {\n",
    "    \"blocks\": [\n",
    "        {\"data\": {\"value\": \"INSTRUCTIONS: Fix up the transcript of the audio in the below text box. The text above the textbox is a hint that usually has the correct formatting (punctuation, hesitation, filler words etc) and the text in the texbox usually has the correct vocabulary (names etc). Listen to the audio and use the text above the textbox to correctly fix the text inside the textbox. Remember to transcribe every single word or word fragment, just as in the text above the texfield.\"}, \"type\": \"markdown\"},\n",
    "        {\"data\": {\"key\": \"url\"}, \"type\": \"audio\", \"props\": {\"complex\": True}},\n",
    "        {\"data\": {\"key\": \"rev_text\"}, \"type\": \"markdown\"},\n",
    "        {\"data\": {\"key\": \"text\"}, \"type\": \"textarea\", \"props\": {\"placeholder\": \"\"}}, \n",
    "    ]\n",
    "}\n",
    "\n",
    "group_tag == \"ami_other\"\n",
    "_df = segments_df[segments_df[\"group_tag\"] == group_tag]\n",
    "\n",
    "p = api.create_project(name=\"turk ami_other\")\n",
    "\n",
    "datums = []\n",
    "for _, row in _df.iterrows():\n",
    "    datums.append({\n",
    "        \"metadata\": {\n",
    "            \"type\": \"audio\",\n",
    "            \"text\": row[\"text\"],\n",
    "            \"rev_text\": row[\"rev_text\"],\n",
    "        },\n",
    "        \"externalId\": row[\"uid\"],\n",
    "        \"storageKey\": f\"studio/projects/{PROJECT_ID}/{row['uid']}.wav\"\n",
    "    })\n",
    "datums_out = p.add_data(datums)\n",
    "\n",
    "# Once created, you can go https://console.suno.ai/ and click on the project and start labeling.\n",
    "task_out = p.add_task_config({'name': 'HF fixup', 'metadata': task_config_meta})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 179,
   "id": "bbd36deb",
   "metadata": {},
   "outputs": [],
   "source": [
    "# task_config_meta = {\n",
    "#     \"blocks\": [\n",
    "#         {\"data\": {\"value\": \"INSTRUCTIONS: Fix up the transcript of the audio in the below text box. The text above the textbox is a hint that usually has the correct formatting (punctuation, hesitation, filler words etc) and the text in the texbox usually has the correct vocabulary (names etc). Listen to the audio and use the text above the textbox to correctly fix the text inside the textbox. Remember to transcribe every single word or word fragment, just as in the text above the texfield. Note: keep partial words and break of thought with double dash -- but not metatags with brackets like [laughter] in the final transcript.\"}, \"type\": \"markdown\"},\n",
    "#         {\"data\": {\"key\": \"url\"}, \"type\": \"audio\", \"props\": {\"complex\": True}},\n",
    "#         {\"data\": {\"key\": \"rev_text\"}, \"type\": \"markdown\"},\n",
    "#         {\"data\": {\"key\": \"text\"}, \"type\": \"textarea\", \"props\": {\"placeholder\": \"\"}}, \n",
    "#     ]\n",
    "# }\n",
    "# p.update_task_config('064749e7-5223-422f-a45f-d3c9c00712fb', {'metadata': task_config_meta})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c309cdb3",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a5586072",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0f296f7c",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4da12fdd",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2018613c",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "200bf9bb",
   "metadata": {},
   "source": [
    "## Playground"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "1a35b70d",
   "metadata": {},
   "outputs": [],
   "source": [
    "group_tag = \"vox_other\"\n",
    "\n",
    "df = segments_df[segments_df[\"group_tag\"] == group_tag].copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "97b87da1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "14.9 % auto matched\n",
      "3.7 minutes\n"
     ]
    }
   ],
   "source": [
    "df[\"is_match\"] = False\n",
    "df.loc[df[\"text_norm\"] == df[\"rev_text_norm\"], \"is_match\"] = True\n",
    "df.loc[\n",
    "    (\n",
    "        df[\"text_norm\"].apply(lambda x: set(x.split())) -\n",
    "        df[\"rev_text_norm\"].apply(lambda x: set(x.split())) - \n",
    "        {\"unk\"}\n",
    "    ).str.len() == 0, \"is_match\"] = True\n",
    "print((df[\"is_match\"].mean() * 100).round(1), \"% auto matched\")\n",
    "print(round(df[df[\"is_match\"]][\"duration_s\"].sum() / 60, 1), \"minutes\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "e4d0bc93",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "215 total\n",
      "183 non-match\n"
     ]
    }
   ],
   "source": [
    "_df = df[~df[\"is_match\"]]\n",
    "print(df.shape[0], \"total\")\n",
    "print(_df.shape[0], \"non-match\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "fe8d5bf5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
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\"/>\n",
       "  Your browser does not support the audio element.\n",
       "</audio>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "raw_text\n",
      "It is also a question of when the authorities perpetrate this kind of violence.\n",
      "\n",
      "asr\n",
      "it is also a question of when the authorities do this kind of violence\n",
      "\n",
      "text\n",
      "It is also a question of when the authorities perpetrate this kind of violence.\n",
      "\n",
      "rev_text\n",
      "And it's also a question of when the authorities do this kind of violence.\n",
      "\n",
      "text_norm\n",
      "it is also a question of when the authorities perpetrate this kind of violence\n",
      "\n",
      "rev_text_norm\n",
      "and it's also a question of when the authorities do this kind of violence\n",
      "\n"
     ]
    }
   ],
   "source": [
    "n = 8\n",
    "\n",
    "row = _df.iloc[n]\n",
    "Audio.from_file(row[\"uri\"]).play()\n",
    "for t in [\"raw_text\", \"asr\", \"text\", \"rev_text\", \"text_norm\", \"rev_text_norm\"]:\n",
    "    print(t)\n",
    "    print(row[t])\n",
    "    print()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "5cb671ea",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "row[\"text_norm\"] == row[\"rev_text_norm\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "19a50ab6",
   "metadata": {},
   "outputs": [],
   "source": [
    "# n = 0\n",
    "\n",
    "l = list(range(df.shape[0]))\n",
    "random.shuffle(l)\n",
    "# row = df.iloc[l[n]]\n",
    "# Audio.from_file(row[\"uri\"]).play()\n",
    "# for t in [\"raw_text\", \"asr\", \"text\", \"text_norm\", \"rev_text\", \"rev_text_norm\"]:\n",
    "#     print(t)\n",
    "#     print(row[t])\n",
    "#     print()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b8cc313c",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3379710d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# earnings22\n",
    "# TODO: remove <unk> when creating\n",
    "# TODO: replace … with ' -- '\n",
    "# for others should we just take ground-truth? and verify by hand?\n",
    "# lots of edge mistakes (fix those via rev?) -- missing a partial word at end\n",
    "# partial words in ground truth need --\n",
    "\n",
    "# vox\n",
    "# stabilizing vs stabilising\n",
    "# edge mistake - first word not in audio\n",
    "# missing disfluencies"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b0083eb1",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a323ad13",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bc449ddd",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1656664f",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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