{
"cells": [
{
"cell_type": "code",
"execution_count": 3,
"id": "157be3b8",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Populating the interactive namespace from numpy and matplotlib\n"
]
}
],
"source": [
"%pylab inline"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "fad832ea",
"metadata": {},
"outputs": [],
"source": [
"import json\n",
"import os\n",
"import numpy as np\n",
"import tqdm\n",
"\n",
"from suno_utils.audio import Audio\n",
"from suno_utils.utils.numbers import safe_round\n",
"\n",
"DATA_DIR = \"/data/suno/data/harvest/youtube_med\""
]
},
{
"cell_type": "code",
"execution_count": 203,
"id": "05ec5798",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 148386/148386 [01:37<00:00, 1524.98it/s]\n"
]
}
],
"source": [
"from suno_utils.harvest.youtube import clean_vtt, clean_cc_lines\n",
"\n",
"data = []\n",
"with open(\"/data/suno/data/harvest/youtube_med/05_audio_metas_post_transcribe_2.jsonl\") as f:\n",
" for line in tqdm.tqdm(f, total=148_386):\n",
" line = line.strip()\n",
" if len(line) == 0:\n",
" continue\n",
" m = json.loads(line)\n",
" if m is None:\n",
" continue\n",
" data.append((m[\"id\"], m[\"audio_filepath_wav\"], m[\"timed_lines\"], m[\"transcript_lines\"]))\n",
"# if len(data) == 100:\n",
"# break\n",
"# break"
]
},
{
"cell_type": "code",
"execution_count": 19,
"id": "2492f51d",
"metadata": {},
"outputs": [],
"source": [
"# # listen to random ones\n",
"# import random\n",
"# l = data[:]\n",
"# random.shuffle(l)\n",
"# for e in l[:5]:\n",
"# ee = e[-1][:]\n",
"# if len(ee) < 3:\n",
"# continue\n",
"# print(e[0])\n",
"# n = random.choice(range(len(ee)-2))\n",
"# for nn in range(n, n+3):\n",
"# print(ee[nn])\n",
"# min_ts = ee[n][0][0]\n",
"# max_ts = ee[n+2][0][1]\n",
"# Audio.from_file(e[1]).play(min_ts, max_ts)\n",
"# print(\"-\"*10)"
]
},
{
"cell_type": "code",
"execution_count": 261,
"id": "6cc26c24",
"metadata": {},
"outputs": [],
"source": [
"n = 4\n",
"audio = Audio.from_file(data[n][1])\n",
"_id, fp, timed_lines, transcript_lines = data[n]"
]
},
{
"cell_type": "code",
"execution_count": 270,
"id": "693cc38d",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"2 segments are reliable\n",
"CPU times: user 897 ms, sys: 67.5 ms, total: 964 ms\n",
"Wall time: 962 ms\n"
]
}
],
"source": [
"%%time\n",
"from suno_utils.utils.text import normalize_whitespace\n",
"from suno_utils.utils.text_normalizer import normalize\n",
"from suno_utils.audio import Tokens\n",
"\n",
"def _simple_norm(text):\n",
"# return normalize_whitespace(re.sub(r\"[^a-z\\s\\']\", \"\", text.lower()))\n",
" return normalize(Tokens.from_text(text)).text \n",
"\n",
"\n",
"n_char_match = 4\n",
"boundary_info = []\n",
"for (_, text), transcript in zip(timed_lines, transcript_lines):\n",
" text_norm = _simple_norm(text)\n",
" transcript_norm = _simple_norm(transcript)\n",
" start_safe = text_norm[:n_char_match] == transcript_norm[:n_char_match]\n",
" end_safe = text_norm[-n_char_match:] == transcript_norm[-n_char_match:]\n",
" # TODO: allow wiggle room 1 word before/after\n",
" boundary_info.append((start_safe, end_safe))\n",
"a, b = zip(*boundary_info)\n",
"is_good_boundary_list = (np.array(a[1:]) & np.array(b[:-1])).tolist()\n",
"is_good_boundary_list.append(b[-1])\n",
"first_is_good_boundary = boundary_info[0][0]\n",
"# assemble segments\n",
"timed_segments = []\n",
"tmp_segments = []\n",
"offs_s = 0\n",
"if first_is_good_boundary and timed_lines[0][0][0] > 0:\n",
" timed_segments.append(((offs_s, timed_lines[0][0][0]), \"\"))\n",
" offs_s = timed_lines[0][0][0]\n",
"for ((ts, te), text), is_b in zip(timed_lines, is_good_boundary_list):\n",
" tmp_segments.append(((ts, te), text))\n",
" if is_b:\n",
" if len(tmp_segments) > 0:\n",
" segment_text = normalize_whitespace(\" \".join([text for _, text in tmp_segments]))\n",
" timed_segments.append(((offs_s, tmp_segments[-1][0][1]), segment_text))\n",
" offs_s = tmp_segments[-1][0][1]\n",
" tmp_segments = []\n",
"if len(tmp_segments) > 0:\n",
" segment_text = normalize_whitespace(\" \".join([text for _, text in tmp_segments]))\n",
" timed_segments.append(((offs_s, audio.duration_s), segment_text))\n",
" tmp_segments = []\n",
"elif offs_s < audio.duration_s:\n",
" timed_segments.append(((offs_s, audio.duration_s), \"\"))\n",
"print(len(timed_segments), \"segments are reliable\")\n",
"# merge segments\n",
"GOAL_DURATION_S = 20\n",
"merged_segments = [timed_segments[0]]\n",
"for (ts, te), text in timed_segments[1:]:\n",
" if te - merged_segments[-1][0][0] <= GOAL_DURATION_S:\n",
" merged_segments[-1] = (\n",
" (\n",
" safe_round(merged_segments[-1][0][0], granularity_s=0.01), \n",
" safe_round(te, granularity_s=0.01)\n",
" ), \n",
" normalize_whitespace(merged_segments[-1][1] + text)\n",
" )\n",
" else:\n",
" merged_segments.append((\n",
" (\n",
" safe_round(ts, granularity_s=0.01), \n",
" safe_round(te, granularity_s=0.01)\n",
" ), \n",
" text\n",
" ))"
]
},
{
"cell_type": "code",
"execution_count": 266,
"id": "70e0d43a",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[([[0.03, 3.69],\n",
" \"In this video, we're going to address some possible situations you might come across while in\"],\n",
" 'in this video we are going to address some possible situations you might come across long'),\n",
" ([[3.69, 9.72],\n",
" \"braces. We're gonna give you some tips and tricks in how this can be alleviated at home. As your\"],\n",
" \"ras we're going to give some tips and chess and how this can be alllegated at\"),\n",
" ([[9.72, 13.65],\n",
" 'teeth shift, the ends of your wires might tend to get longer and can start poking and irritating'],\n",
" 'your teeth shift the ends of your wires might tend to get longer and can start poking irrit'),\n",
" ([[13.65, 19.11],\n",
" 'your cheeks. If this happens, you can place wax on the poking area, and/or try to clip it using'],\n",
" 'your cheeks if this happens you can place wax on the poking area and or try to clip it'),\n",
" ([[19.11, 24.15],\n",
" 'a disinfected nail cutter or a small wire cutter. If enabled to, give your ortho office a call so'],\n",
" 'a disinfected noil cutter or a small wire cutter if un able to give you orto office the call'),\n",
" ([[24.15, 28.98],\n",
" 'they can schedule a short visit and clip it for you. Remember, most braces-related issues can be'],\n",
" 'so they can schedule a short visit and clip it for you remember most braces related issues can'),\n",
" ([[28.98, 34.02],\n",
" 'taken care of at home. However, you should still contact your orthodontic team; sending a photo of'],\n",
" 'be taking care of at home however you should still contact your orthodonic team s phot'),\n",
" ([[34.02, 38.19],\n",
" 'your problem area can help the team guide you to solve the problem or schedule you an appointment.'],\n",
" 'of your problem area can help the team guide you to solve the problem or schedule your')]"
]
},
"execution_count": 266,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"list(zip(timed_lines, transcript_lines))"
]
},
{
"cell_type": "code",
"execution_count": 263,
"id": "d8d01187",
"metadata": {},
"outputs": [],
"source": [
"# [safe_round(te - ts, granularity_s=0.01) for (ts, te), text in merged_segments]"
]
},
{
"cell_type": "code",
"execution_count": 264,
"id": "7e1b5094",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n"
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"0 0.03\n",
"\n",
"----------\n"
]
},
{
"data": {
"text/html": [
"\n",
"\n"
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"0.0 38.19\n",
"In this video, we're going to address some possible situations you might come across while in braces. We're gonna give you some tips and tricks in how this can be alleviated at home. As your teeth shift, the ends of your wires might tend to get longer and can start poking and irritating your cheeks. If this happens, you can place wax on the poking area, and/or try to clip it using a disinfected nail cutter or a small wire cutter. If enabled to, give your ortho office a call so they can schedule a short visit and clip it for you. Remember, most braces-related issues can be taken care of at home. However, you should still contact your orthodontic team; sending a photo of your problem area can help the team guide you to solve the problem or schedule you an appointment.\n",
"----------\n"
]
},
{
"data": {
"text/html": [
"\n",
"\n"
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"38.19 41.98\n",
"\n",
"----------\n"
]
}
],
"source": [
"for (ts, te), text in merged_segments:\n",
" audio.get_slice(ts, te).play()\n",
" print(ts, te)\n",
" print(text)\n",
" print(\"-\"*10)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "a2e4fd42",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"id": "178d2954",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"id": "a0c1fd5e",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"id": "f0f82e11",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"id": "541edf28",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"id": "39d1c439",
"metadata": {},
"source": [
"### refine vad cut"
]
},
{
"cell_type": "code",
"execution_count": 185,
"id": "90880895",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"CPU times: user 1.04 s, sys: 0 ns, total: 1.04 s\n",
"Wall time: 1.04 s\n"
]
}
],
"source": [
"%%time\n",
"# 1s for 340s audio\n",
"audio_array = audio.array_float\n",
"collar_s = 0.4\n",
"adjusted_ts_s = []\n",
"cache_dict = {}\n",
"for (ts, te), text in data[n][2]:\n",
" if ts in cache_dict:\n",
" pass\n",
" elif ts - collar_s < 0:\n",
" cache_dict[ts] = ts\n",
" else:\n",
" cache_dict[ts] = (\n",
" ts - collar_s + \n",
" get_vad_break(\n",
" vad_model, \n",
" audio_array[int((ts-collar_s)*SAMPLE_RATE):int((ts+collar_s)*SAMPLE_RATE)], \n",
" min_p=0.5, \n",
" min_streak=1,\n",
" )\n",
" )\n",
" ts_new = cache_dict[ts]\n",
" if te in cache_dict:\n",
" pass\n",
" elif te + collar_s > audio.duration_s:\n",
" cache_dict[te] = te\n",
" else:\n",
" cache_dict[te] = (\n",
" te - collar_s + \n",
" get_vad_break(\n",
" vad_model, \n",
" audio_array[int((te-collar_s)*SAMPLE_RATE):int((te+collar_s)*SAMPLE_RATE)], \n",
" min_p=0.5, \n",
" min_streak=1,\n",
" )\n",
" )\n",
" te_new = cache_dict[te]\n",
" adjusted_ts_s.append((safe_round(ts_new, granularity_s=0.001), safe_round(te_new, granularity_s=0.001)))\n",
"# break"
]
},
{
"cell_type": "code",
"execution_count": 139,
"id": "206cf568",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[((0.11, 1.94), \"Hey guys, I'm really passionate\"),\n",
" ((1.94, 3.57), 'about living a healthy lifestyle,')]"
]
},
"execution_count": 139,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data[n][-1][:2]"
]
},
{
"cell_type": "code",
"execution_count": 140,
"id": "1382ac41",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[(0.11, 1.94), (1.94, 3.4)]"
]
},
"execution_count": 140,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"adjusted_ts_s[:2]"
]
},
{
"cell_type": "code",
"execution_count": 142,
"id": "b19dc741",
"metadata": {
"scrolled": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Hey guys, I'm really passionate (0.11, 1.94)\n"
]
},
{
"data": {
"text/html": [
"\n",
"\n"
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"\n",
"\n"
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"----------\n",
"about living a healthy lifestyle, (1.94, 3.57)\n"
]
},
{
"data": {
"text/html": [
"\n",
"\n"
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"\n",
"\n"
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"----------\n"
]
}
],
"source": [
"for (old, text), new in zip(\n",
" [((ts, te), text) for (ts, te), text in data[n][-1]],\n",
" adjusted_ts_s[:2],\n",
"):\n",
" print(text, old)\n",
" audio.get_slice(*old).play()\n",
" audio.get_slice(*new).play()\n",
" print(\"-\"*10)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "32ac433c",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"id": "97ea8ba8",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"id": "9ca5000c",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"id": "181e43f3",
"metadata": {},
"source": [
"## nemo vad"
]
},
{
"cell_type": "code",
"execution_count": 72,
"id": "cf5d0705",
"metadata": {},
"outputs": [],
"source": [
"import contextlib\n",
"\n",
"import numpy as np\n",
"import nemo.collections.asr as nemo_asr\n",
"import torch\n",
"\n",
"from suno_utils.utils.display import suppress_logging\n",
"\n",
"if (\n",
" torch.cuda.is_available()\n",
" and hasattr(torch.cuda, \"amp\")\n",
" and hasattr(torch.cuda.amp, \"autocast\")\n",
"):\n",
" autocast = torch.cuda.amp.autocast\n",
"else:\n",
" @contextlib.contextmanager\n",
" def autocast():\n",
" yield\n",
"\n",
"\n",
"def load_model(model_name=\"vad_multilingual_marblenet\"):\n",
" with suppress_logging():\n",
" model = nemo_asr.models.EncDecClassificationModel.from_pretrained(model_name=model_name)\n",
" model.preprocessor.featurizer.dither = 0.0\n",
" model.preprocessor.featurizer.pad_to = 0\n",
" model.eval()\n",
" model.encoder.freeze()\n",
" model.decoder.freeze()\n",
" torch.cuda.synchronize()\n",
" torch.cuda.empty_cache()\n",
" return model\n",
"\n",
"\n",
"SAMPLE_RATE = 16_000\n",
"WINDOW_LENGTH_S = 0.2\n",
"SHIFT_LENGTH_S = 0.01\n",
"\n",
"\n",
"def array_chunks(chunksize, arr, keep_all=True, shift_len=None):\n",
" if shift_len is None:\n",
" shift_len = chunksize\n",
" for pos in range(0, len(arr), shift_len):\n",
" if not keep_all and len(arr[pos:]) < chunksize:\n",
" break\n",
" yield arr[pos:pos+chunksize]\n",
"\n",
"\n",
"def get_vad_preds(\n",
" model,\n",
" audio_arr,\n",
" window_length_s=WINDOW_LENGTH_S,\n",
" shift_length_s=SHIFT_LENGTH_S,\n",
" sample_rate=SAMPLE_RATE,\n",
"):\n",
" window_length = int(window_length_s * sample_rate)\n",
" shift_length = int(shift_length_s * sample_rate)\n",
" arr_list = list(array_chunks(window_length, audio_arr, keep_all=False, shift_len=shift_length))\n",
" if len(arr_list) == 0:\n",
" return np.empty(0), np.empty(0)\n",
" x_time_s = np.array([\n",
" ((window_length / 2) + n * shift_length) / sample_rate for n in range(len(arr_list))\n",
" ])\n",
" with torch.inference_mode(), torch.no_grad(), autocast():\n",
" arr_gpu = torch.from_numpy(np.vstack(arr_list)).to(model.device)\n",
" arr_len_gpu = torch.tensor([arr.shape[0] for arr in arr_list]).to(model.device)\n",
" log_probs = model(input_signal=arr_gpu, input_signal_length=arr_len_gpu)\n",
" probs = torch.softmax(log_probs, dim=-1)\n",
" y_is_speech_p = probs[:, 1].detach().cpu().numpy()\n",
" del arr_gpu, arr_len_gpu, log_probs, probs\n",
" torch.cuda.synchronize()\n",
" return x_time_s, y_is_speech_p\n",
"\n",
"\n",
"def get_best_silence_index(arr, min_p=0.2, min_streak=2):\n",
" streaks = []\n",
" prev_idx = -2\n",
" for idx in np.where(arr <= min_p)[0]:\n",
" if idx == prev_idx + 1:\n",
" streaks[-1] = (streaks[-1][0], streaks[-1][1] + 1)\n",
" else:\n",
" streaks.append((idx, 1))\n",
" prev_idx = idx\n",
" streaks = [(streak_idx, streak_len) for streak_idx, streak_len in streaks if streak_len >= min_streak]\n",
" streaks = sorted(streaks, key=lambda x: x[1], reverse=True)\n",
" if len(streaks) == 0:\n",
" return None\n",
" return streaks[0][0] + int((streaks[0][1] - 1) / 2)\n",
"\n",
"\n",
"def get_vad_break(model, audio_arr, min_p=0.2, min_streak=2):\n",
" x_time_s, y_is_speech_p = get_vad_preds(model, audio_arr)\n",
" best_idx = get_best_silence_index(y_is_speech_p, min_p=min_p, min_streak=min_streak)\n",
" if best_idx is not None:\n",
" return x_time_s[best_idx]\n",
" else:\n",
" return x_time_s[int(len(x_time_s) / 2)]\n",
" \n",
"vad_model = load_model()"
]
},
{
"cell_type": "code",
"execution_count": 53,
"id": "a8a9ef02",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"x_time_s, y_is_speech_p = get_vad_preds(vad_model, audio.get_slice(te-collar_s, te+collar_s).array_float)\n",
"plt.plot(x_time_s, y_is_speech_p);"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "b6299aa6",
"metadata": {},
"outputs": [
{
"ename": "NameError",
"evalue": "name 'audio' is not defined",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m/tmp/ipykernel_387349/2000731660.py\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0mbreak_guess_s\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m21.53\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[0mcollar_s\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m0.2\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0maudio_segment\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0maudio\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_slice\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbreak_guess_s\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0mcollar_s\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbreak_guess_s\u001b[0m\u001b[0;34m+\u001b[0m\u001b[0mcollar_s\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[0;31mNameError\u001b[0m: name 'audio' is not defined"
]
}
],
"source": [
"break_guess_s = 21.53\n",
"collar_s = 0.2\n",
"audio_segment = audio.get_slice(break_guess_s-collar_s, break_guess_s+collar_s)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "cba0ba98",
"metadata": {},
"outputs": [
{
"ename": "NameError",
"evalue": "name 'vad_model' is not defined",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m/tmp/ipykernel_387349/3378494922.py\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mbreak_guess_s\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0mcollar_s\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mget_vad_break\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvad_model\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maudio_segment\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[0;31mNameError\u001b[0m: name 'vad_model' is not defined"
]
}
],
"source": [
"break_guess_s - collar_s + get_vad_break(vad_model, audio_segment.array_float)"
]
},
{
"cell_type": "code",
"execution_count": 707,
"id": "f316cf91",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n"
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"audio.play(20, 21.655)"
]
},
{
"cell_type": "code",
"execution_count": 728,
"id": "52aac61c",
"metadata": {},
"outputs": [],
"source": [
"a1 = audio.get_slice(20, 21.53).array_float[:16_000]\n",
"a2 = np.zeros(a1.shape[0], dtype=a1.dtype)\n",
"a = np.hstack([a1, a2, a1])\n",
"aa = Audio.from_array_float(a, sample_rate=16_000)"
]
},
{
"cell_type": "code",
"execution_count": 730,
"id": "6d28721b",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"1.51"
]
},
"execution_count": 730,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"get_vad_break(vad_model, aa)"
]
},
{
"cell_type": "code",
"execution_count": 729,
"id": "dd2f63de",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"x_time_s, y_is_speech_p = get_vad_preds(vad_model, aa)\n",
"plt.plot(x_time_s, y_is_speech_p);"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "526e0b42",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"id": "a1bac8e7",
"metadata": {},
"outputs": [],
"source": [
"# did we kill a hellow too many?\n",
"# ZHmtvR-1ivw\n",
"# ((252.92, 255.13), 'Hello, anyone there?')\n",
"# ((255.297, 257.549), 'Hello?')\n",
"# ((262.596, 264.139), 'Do you folks need some help?')"
]
},
{
"cell_type": "code",
"execution_count": 626,
"id": "a96933fb",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"WEBVTT\n",
"Kind: captions\n",
"Language: en\n",
"\n",
"00:00:04.338 --> 00:00:05.422\n",
"[crying]\n",
"\n",
"00:00:09.259 --> 00:00:12.346\n",
"Way! Wook! It’s Widward!\n",
"\n",
"00:00:12.429 --> 00:00:13.222\n",
"What?\n",
"\n",
"00:00:13.305 --> 00:00:16.183\n",
"[laughing]\n",
"\n",
"00:00:16.308 --> 00:00:20.020\n",
"What's that supposed to be?\n",
"Some kind of stupid secret code?\n",
"\n",
"00:00:20.103 --> 00:00:22.981\n",
"We can’t tell you because\n",
"you're not a member of the club.\n",
"\n",
"00:00:23.065 --> 00:00:25.943\n",
"Oh, yeah?\n",
"What does it take to be a member?\n",
"\n",
"00:00:26.026 --> 00:00:30.364\n",
"Squidward, you and your nose\n",
"will definitely not fit in.\n",
"\n",
"00:00:30.447 --> 00:00:33.784\n",
"Oh, what do you to zeroes know\n",
"about fitting in?\n",
"\n",
"00:00:34.034 --> 00:00:37.287\n",
"Why, you should be begging me to join.\n",
"\n",
"00:00:37.788 --> 00:00:40.707\n",
"- You can’t join! Can’t join!\n",
"- You can’t get in!\n",
"\n",
"00:00:40.874 --> 00:00:43.001\n",
"[groaning]\n",
"\n",
"00:00:44.586 --> 00:00:48.048\n",
"Well, this is stupid!\n",
"There's no room up here!\n",
"\n",
"00:00:48.674 --> 00:00:51.301\n",
"That's what we've been trying to tell you.\n",
"\n",
"00:00:51.385 --> 00:00:53.470\n",
"I do not now,\n",
"\n",
"00:00:53.720 --> 00:00:57.224\n",
"nor will I ever want to be\n",
"\n",
"00:00:57.266 --> 00:01:01.436\n",
"a member of your stupid club!\n",
"\n",
"00:01:05.774 --> 00:01:11.488\n",
"[screaming]\n",
"\n",
"00:01:18.537 --> 00:01:21.707\n",
"Oh no, that didn’t just happen.\n",
"Please tell me that didn't happen.\n",
"\n",
"00:01:21.748 --> 00:01:23.750\n",
"What happened?\n",
"\n",
"00:01:23.834 --> 00:01:26.128\n",
"Where are we? We’re lost!\n",
"There's no way out.\n",
"\n",
"00:01:26.211 --> 00:01:31.175\n",
"We’re stuck in the middle\n",
"of nowhere with SpongeBob and Patrick.\n",
"\n",
"00:01:32.843 --> 00:01:34.761\n",
"Well, this is the end.\n",
"\n",
"00:01:36.013 --> 00:01:37.806\n",
"No, it’s not Squidward.\n",
"\n",
"00:01:37.890 --> 00:01:39.474\n",
"It’s not?\n",
"\n",
"00:01:39.558 --> 00:01:43.145\n",
"- We have this!\n",
"- How can that possibly help us?\n",
"\n",
"00:01:43.228 --> 00:01:44.897\n",
"Oh, Squidward.\n",
"\n",
"00:01:44.980 --> 00:01:47.649\n",
"We must never question\n",
"the wisdom of the magic conch.\n",
"\n",
"00:01:47.733 --> 00:01:50.819\n",
"The club always take its advice\n",
"before we do anything.\n",
"\n",
"00:01:50.903 --> 00:01:52.988\n",
"Oh, magic conch shell,\n",
"\n",
"00:01:53.071 --> 00:01:56.408\n",
"what do we need to do\n",
"to get out of the kelp forest?\n",
"\n",
"00:01:59.203 --> 00:02:02.414\n",
"- Nothing.\n",
"- The shell has spoken.\n",
"\n",
"00:02:02.497 --> 00:02:06.960\n",
"Nothing. We can't just sit\n",
"here and do nothing!\n",
"\n",
"00:02:09.338 --> 00:02:10.714\n",
"Ugh!\n",
"\n",
"00:02:10.797 --> 00:02:14.051\n",
"I am going to find my way back to sanity!\n",
"\n",
"00:02:14.134 --> 00:02:18.931\n",
"But don’t you two sad clowns come crying\n",
"to me when your circus tent comes\n",
"\n",
"00:02:19.014 --> 00:02:22.643\n",
"crashing down. Sad clown. Ha.\n",
"\n",
"00:02:22.726 --> 00:02:23.644\n",
"[laughing]\n",
"\n",
"00:02:27.105 --> 00:02:28.524\n",
"I’m free!\n",
"\n",
"00:02:28.607 --> 00:02:29.858\n",
"[laughing]\n",
"\n",
"00:02:30.025 --> 00:02:32.861\n",
"Take that, SpongeBob and Patrick!\n",
"\n",
"00:02:33.403 --> 00:02:34.780\n",
"[laughing]\n",
"\n",
"00:02:38.659 --> 00:02:41.245\n",
"Yeah, huh? Oh.\n",
"\n",
"00:02:43.038 --> 00:02:47.501\n",
"Dude! We’re falling right outta the sky.\n",
"We’ve gotta drop the load!\n",
"\n",
"00:03:01.807 --> 00:03:04.393\n",
"Praise the magic conch!\n",
"\n",
"00:03:11.400 --> 00:03:13.902\n",
"Mmm mm.\n",
"\n",
"00:03:15.988 --> 00:03:18.073\n",
"Oh my! What shall I eat first?\n",
"The spaghetti,\n",
"\n",
"00:03:18.156 --> 00:03:19.992\n",
"the turkey, the soup, the canned meat?\n",
"\n",
"00:03:20.075 --> 00:03:23.287\n",
"Why don’t you ask the\n",
"magic conch, Squidward?\n",
"\n",
"00:03:23.370 --> 00:03:26.832\n",
"Oh, yeah, like that’ll happen.\n",
"Right after I consult the magic toenail.\n",
"\n",
"00:03:26.915 --> 00:03:28.792\n",
"[gasping]\n",
"\n",
"00:03:29.418 --> 00:03:34.798\n",
"Squidward, are you questioning\n",
"the authority of the magic conch?\n",
"\n",
"00:03:34.882 --> 00:03:35.924\n",
"[laughing]\n",
"\n",
"00:03:36.008 --> 00:03:40.971\n",
"You guys have it all wrong.\n",
"I love this... piece of plastic.\n",
"\n",
"00:03:41.054 --> 00:03:42.306\n",
"Uh.\n",
"\n",
"00:03:42.389 --> 00:03:43.599\n",
"Hello there,\n",
"\n",
"00:03:43.724 --> 00:03:44.850\n",
"magic conch,\n",
"\n",
"00:03:44.975 --> 00:03:50.022\n",
"I was wondering uh… should I have\n",
"those spaghetti or the turkey?\n",
"\n",
"00:03:50.647 --> 00:03:51.690\n",
"Neither.\n",
"\n",
"00:03:51.773 --> 00:03:54.067\n",
"Oh. Then how about that soup?\n",
"\n",
"00:03:54.735 --> 00:03:56.069\n",
"I don't think so.\n",
"\n",
"00:03:56.403 --> 00:03:58.488\n",
"- Could I have anything to eat?\n",
"- No.\n",
"\n",
"00:03:58.572 --> 00:04:02.159\n",
"- Could I have something to eat.\n",
"- No.\n",
"\n",
"00:04:02.242 --> 00:04:05.537\n",
"- Ugh!!\n",
"\n",
"00:04:05.621 --> 00:04:08.248\n",
"Squidward, are you alright?\n",
"\n",
"00:04:09.333 --> 00:04:11.835\n",
"Maybe we should ask the\n",
"shell if he’s okay.\n",
"\n",
"00:04:12.920 --> 00:04:15.130\n",
"Hello, anyone there?\n",
"\n",
"00:04:15.297 --> 00:04:17.549\n",
"Hello?\n",
"\n",
"00:04:19.510 --> 00:04:20.427\n",
"[gasping]\n",
"\n",
"00:04:22.596 --> 00:04:24.139\n",
"Do you folks need some help?\n",
"\n",
"00:04:24.723 --> 00:04:29.019\n",
"I’m saved! You don’t know how happy I am\n",
"to see you!\n",
"\n",
"00:04:29.144 --> 00:04:34.316\n",
"I have been stranded out here for\n",
"weeks with these two barnacle heads\n",
"\n",
"00:04:34.483 --> 00:04:39.404\n",
"- and their magic conch shell.\n",
"- Magic conch shell?\n",
"\n",
"00:04:40.030 --> 00:04:42.074\n",
"You mean like this?\n",
"\n",
"00:04:42.157 --> 00:04:46.203\n",
"The magic conch! A club member!\n",
"\n",
"00:04:46.954 --> 00:04:47.913\n",
"[moaning]\n",
"\n",
"00:04:47.996 --> 00:04:49.915\n",
"Alright, magic conch.\n",
"\n",
"00:04:49.998 --> 00:04:51.834\n",
"What do we do now?\n",
"\n",
"00:04:53.544 --> 00:04:54.795\n",
"Nothing.\n",
"\n",
"00:04:55.212 --> 00:04:58.090\n",
"Oh hail, the magic conch!\n",
"\n",
"00:05:04.012 --> 00:05:06.932\n",
"Oh hail, the magic conch!\n",
"\n",
"\n"
]
}
],
"source": [
"with open(\"/data/suno/data/harvest/youtube_med/audio/ZHmtvR-1ivw.en.vtt\") as f:\n",
" print(f.read())"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "8e64af4d",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"id": "70c80347",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"id": "ca783d82",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"id": "b0b3b497",
"metadata": {},
"source": [
"## Playground"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "4197131a",
"metadata": {},
"outputs": [],
"source": [
"# l = []\n",
"# n = 0\n",
"# with open(os.path.join(DATA_DIR, \"videos_urls.jsonl\")) as f:\n",
"# for line in f:\n",
"# line = line.strip()\n",
"# if len(line) == 0:\n",
"# continue\n",
"# m = json.loads(line)\n",
"# if m[\"success\"]:\n",
"# for mm in m[\"search_results\"]:\n",
"# l.append(mm[\"id\"])\n",
"# n += len(m[\"search_results\"])\n",
"# # break\n",
"\n",
"# print(n, \"videos\")\n",
"# print(len(set(l)), \"unique\")"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "7c36ee00",
"metadata": {},
"outputs": [],
"source": [
"# def _parse_duration(s):\n",
"# if s is None:\n",
"# return 0\n",
"# parts = s.split(\":\")\n",
"# if len(parts) == 3:\n",
"# nh, nm, ns = parts\n",
"# elif len(parts) == 2:\n",
"# nm, ns = parts\n",
"# nh = 0\n",
"# else:\n",
"# raise ValueError(\"\")\n",
"# return int(nh) * 60**2 + int(nm) * 60 + int(ns)\n",
"\n",
"# youtube_ids = set()\n",
"# tot_n = 0\n",
"# durations_s = []\n",
"# failed_ids = []\n",
"# with open(os.path.join(DATA_DIR, \"videos_urls.jsonl\")) as f:\n",
"# for l in tqdm.tqdm(f):\n",
"# if len(l.strip()) == 0:\n",
"# continue\n",
"# m = json.loads(l)\n",
"# if m is None:\n",
"# continue\n",
"# if not m[\"success\"]:\n",
"# continue\n",
"# for mm in m[\"search_results\"]:\n",
"# if mm[\"id\"] not in youtube_ids:\n",
"# try:\n",
"# ds = _parse_duration(mm[\"duration\"])\n",
"# except:\n",
"# failed_ids.append(mm[\"id\"])\n",
"# continue\n",
"# durations_s.append(ds)\n",
"# youtube_ids.add(mm[\"id\"])\n",
"# tot_n += 1\n",
"# youtube_ids = list(youtube_ids)\n",
"# print(tot_n, \"videos found\")\n",
"# print(len(youtube_ids), \"unique\")\n",
"# print(len(failed_ids), \"failed\")\n",
"# print(round(np.sum(durations_s) / 60 / 60, 1), \"hours of data\")\n",
"# print(round(np.clip(np.array(durations_s), a_max=3600, a_min=0).sum() / 60 / 60, 1), \"hours of data with clipping\")"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "25ff7fc4",
"metadata": {},
"outputs": [],
"source": [
"# with open(os.path.join(DATA_DIR, \"videos_urls.jsonl\")) as f:\n",
"# for line in tqdm.tqdm(f):\n",
"# if \"HjUBP5l_2Ys\" in line:\n",
"# m = json.loads(line)\n",
"# for mm in m[\"search_results\"]:\n",
"# if \"HjUBP5l_2Ys\" in str(mm):\n",
"# print(mm)\n",
"# break\n",
"# break"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "f8093643",
"metadata": {},
"outputs": [],
"source": [
"# TODO: HjUBP5l_2Ys is spanish with english subtitles...\n",
"# figure out how to get video languages!!\n",
"# https://stackoverflow.com/questions/47105402/is-it-possible-to-obtain-the-spoken-language-from-youtube-dl\n",
"# TODO: YOgIA4Drgi0 says human but looks auto gen-ed??? Sentel vs Zentel (probably uploaded from zoom)\n",
"# TODO: e1FXfvaK9no multilingual zoom"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "6bdb2a62",
"metadata": {},
"outputs": [],
"source": [
"# import youtube_dl\n",
"# YDL_OPTS = {\n",
"# \"format\": \"worstaudio\",\n",
"# \"outtmpl\": \"tmp/%(id)s.%(ext)s\",\n",
"# \"writesubtitles\": True,\n",
"# \"allsubtitles\": True,\n",
"# \"subtitlesformat\": \"best\",\n",
"# \"socket_timeout\": 5.0,\n",
"# }\n",
"# youtube_id = \"YOgIA4Drgi0\"\n",
"# url = \"https://www.youtube.com/watch?v=\" + youtube_id\n",
"# with youtube_dl.YoutubeDL(YDL_OPTS) as ydl:\n",
"# info = ydl.extract_info(url, download=True)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "4a200e4b",
"metadata": {},
"outputs": [],
"source": [
"# filter out super low view count\n",
"# filter out CCs with all upper/lower\n",
"# filter out CCs with word by word timings? zoom asr uploads\n",
"# filter out ones where duration/words does not seem realistic\n",
"# or similar max cer\n",
"# TODO: how to filter out multi lingual?"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "e866ef09",
"metadata": {},
"outputs": [],
"source": [
"# l = []\n",
"# with open(\"/data/suno/data/harvest/youtube_med/audio_metas.jsonl\") as f:\n",
"# for line in f:\n",
"# # if \"HjUBP5l_2Ys\" in line:\n",
"# m = json.loads(line)\n",
"# if not m[\"success\"]:\n",
"# continue\n",
"# fp = os.path.join(\"/data/suno/data/harvest/youtube_med/audio\", m[\"id\"] + \".en.vtt\")\n",
"# fp_from_audio = os.path.join(\"/data/suno/data/harvest/youtube_med/audio\", m[\"id\"] + \".webm\")\n",
"# fp_to_audio = os.path.join(\"tmp_100\", m[\"id\"] + \".webm\")\n",
"# if not os.path.exists(fp) or not os.path.exists(fp_from_audio):\n",
"# continue\n",
"# duration_s = Audio.get_details(fp_from_audio)[\"duration_s\"]\n",
"# if duration_s <= 20 or duration_s >= 5*60:\n",
"# continue\n",
"# with open(fp) as f:\n",
"# s = f.read()\n",
"# shutil.copy(fp_from_audio, fp_to_audio)\n",
"# # ll = [mm for mm in m[\"meta\"][\"subtitles\"].get(\"en\", []) if mm[\"ext\"] == \"vtt\"]\n",
"# # if len(ll) > 0:\n",
"# l.append((m, s))\n",
" \n",
"# if len(l) >= 100:\n",
"# break"
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "84b18a39",
"metadata": {},
"outputs": [],
"source": [
"# n_total = 0\n",
"# n_suspicious = 0\n",
"# mistakes = []\n",
"# with open(\"/data/suno/data/harvest/youtube_med/02_audio_metas_post_norm.jsonl\") as f:\n",
"# for line in f:\n",
"# line = line.strip()\n",
"# if len(line) == 0:\n",
"# continue\n",
"# m = json.loads(line)\n",
"# if m is None:\n",
"# continue\n",
"# text = \" \".join([e for _, e in m[\"timed_lines\"]])\n",
"# n_mistakes = 0\n",
"# mistakes.extend(re.findall(r\".{10}[a-z]{4}\\. [a-z].{,10}\", text))\n",
"# n_mistakes += len(re.findall(r\"[a-z]{4}\\. [a-z]\", text))\n",
"# n_mistakes += text.count(\"per cent\")\n",
"# if n_mistakes >= 2:\n",
"# n_suspicious += 1\n",
"# n_total += 1\n",
"# print(f\"{n_suspicious}/{n_total} suspicious\")\n",
"# print(f\"{n_suspicious/n_total*100}% dropped\")"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "b7b0cc5b",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"b'í'"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"\"í\".encode('ascii', 'xmlcharrefreplace')"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "4585cde4",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
" 2%|██▎ | 2837/148386 [00:00<00:27, 5374.55it/s]"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"6u8eTiP_iWA\n",
"When youíre trading options, especially if youíre a beginner,\n",
"With long calls you have to correctly predict short-term stock behavior, which isnít easy. Naked\n",
"spreads, and theyíre popular because they allow you to define your risk and reward.\n",
"Weíre going to focus on one of the most common: the bull put spread, or as we like to call it,\n",
"such as a credit put spread or short put spread, but itís a basic concept: You sell one put to\n",
"which provides protection in case it doesnít. This allows you to define your risk and your reward.\n",
"Iím Education Coach Cameron May, and Iíve been teaching traders about options for 15 years.\n",
"weíre going to walk through all the ins and outs. Weíll break down how the short put vertical works\n",
"Itís got a lot of the powerful options trading tools of thinkorswim desktop\n",
"Weíll assume you already know the basics of options trading and the greeks. If\n",
"youíre an absolute beginner, check out our other videos to get your bearings on options basics.\n",
"expiration thatís further out of the money. The short put is the driver of the trade. It benefits\n",
"Youíll have to pay the premium for the long put, but that part of the trade is\n",
"usually cheaper than the short put, so youíll wind up with a net credit from the get-go.\n",
"Keep in mind, youíll still have to pay transaction costs. The ideal outcome is for the stock to stay\n",
"you received when you entered the trade. If things donít go your way and your short\n",
"to sell the underlying stock at the strike price. Itís also possible the stock could end up between\n",
"the strikes. This can be a tricky situation, and weíll walk through ways to handle it later.\n",
"But now that youíre familiar with the basic mechanics of the short put vertical,\n",
"As long as you play your strikes right, thereís a relatively high probability of being profitable.\n",
"Letís look at the strategyís risk profile to see how this works.\n",
"mean when I call this a defined risk and reward strategy. Youíre basically capping your potential\n",
"letting you manage how much profit youíre willing to trade for what probability of success you want.\n",
"letís look at an example. Letís say youíre bullish on stock XYZ, and itís currently trading at $99.\n",
"You think itís going to hold steady or move up slightly, so you sell a put 40 days from\n",
"Letís say youíre right, and the stock does increase slightly, up to $101 near expiration.\n",
"leaving you with your $90 credit, minus commissions and fees. Weíll talk about how\n",
"moves down instead? Letís say the stock drops and is trading at $93 at expiration. If that happens,\n",
"your short put is assigned, meaning youíd have to buy 100 shares of the underlying.\n",
"for a lower strike price, youíll only be out the distance between the two strikes.\n",
"Letís break that down by the numbers. Your short put would cost you $9,700 to buy the 100 shares,\n",
"down to $50 per share or lower that $110 is the most youíll lose on this spread.\n",
"Youíll have an in-the-money short put and an out-of-the-money long put.\n",
"ultimately still be profitable, but it might not be. Whatís most important is that youíre at risk\n",
"youíve got a couple choices. You could let the trade expire and get assigned 100 shares of stock.\n",
"But because your goal is not to enter a stock position, youíll probably want to take some\n",
"Now that youíre familiar with potential outcomes of a short put vertical, letís take a quick\n",
"itís theta positive. Remember, the max gain for this strategy is the premium\n",
"have negative vega, so, ideally, youíd like to see volatility hold steady or fall.\n",
"Now that youíve got the basics, letís make some paper trades.\n",
"Iíll log in to thinkorswim Web. Here you can see all the accounts and positions,\n",
"and that Iím in paperMoney, which allows me to place simulated trades without risking real money.\n",
"Iím going to close this sidebar to give us some more room.\n",
"we donít need to own the stock, but we do want to make sure itís following some entry rules.\n",
"uptrend. Of course, thereís no guarantee that the upward trend will continue, but it could\n",
"Next, weíve got to determine when to actually enter the trade.\n",
"For today weíll use Expedia, symbol EXPE, as an example. Hereís its 6 month daily chart.\n",
"You can see itís in an upward trend. Let me draw a trendline here to show what I mean.\n",
"Iíll draw another trendline here, so we can see that itís broken through that ceiling.\n",
"So, we know what stock we want to trade, now weíve got to choose our options contracts.\n",
"To do that Iíll scroll up and open the option chain.\n",
"and stay out of the money. There is a trade-off at play here: We could choose an expiration thatís\n",
"more premium but slower time decay. For a good balance, Iíll aim for an expiration thatís 15\n",
"to 50 days out. So, in this case, weíll go with the March 19 expiration, expiring in 36 days.\n",
"which significantly limits profits. For our short put, weíll look for a delta between .30\n",
"is less than 10% of the ask price, which suggests good liquidity. So letís plan to sell that one,\n",
"so Iíll click the bid price. You can see itís entered at the bottom of the screen.\n",
"Thereís another tradeoff here. The width of the spread determines how much credit weíll receive\n",
"$2 below the short put. For us, the next available strike is $5 away, at 135. Itís allowing us some\n",
"breathing room. Iíll click the ask price. Youíll notice our order now says vertical.\n",
"Letís scroll down and look at it. So, here in the order editor I can see Iím selling the March\n",
"19 140 and buying the March 19 135. Now youíll notice the price of our spread is still moving.\n",
"Letís lock our required credit to a limit of 165. And weíll leave the time in force at day.\n",
"your portfolio risk and your trade risk. Portfolio risk is the total amount of your portfolio youíre\n",
"trading portfolio per trade. So, for simplicity, letís say Iím trading with a $100,000 portfolio.\n",
"If Iím willing to lose no more than 1%, my portfolio risk would be $1,000 per trade.\n",
"In other words, the spread width minus the credit. For this trade thatís a $5 wide spread, or $500\n",
"which Iíll enter in the trade ticket. Now that weíve got our trade loaded up,\n",
"letís do some quick analysis using a nifty feature on thinkorswim web.\n",
"Below the order ticket youíll see a stock chart and a risk profile chart.\n",
"fall in relation to the stockís historical price. You can also hover your mouse over either chart to\n",
"itíll be about 138 and half, 138.35 to be precise, not accounting for the transaction\n",
"direction, anywhere below 135 at expiration, both options would be in the money and Iíd hit max loss\n",
"Letís go back up and place the trade. Iíll click review and confirm the details are\n",
"correct. Note the transaction fee, in this case 3.90, or .65 per contract. Now Iíll click send.\n",
"Thereís the confirmation saying our orderís been sent. Ok, weíve placed a short put vertical!\n",
"But this isnít a set it and forget it kind of strategy. Weíve got to make sure weíre keeping\n",
"up with it. The way you manage these trades can make or break them, so weíre going to\n",
"walk through managing some other sample short put verticals that Iíve got in a paperMoney account.\n",
"But before we go through them, letís talk about a simple rule that can guide how you manage your\n",
"short put spreads: If youíre more than five to 10 days from expiration, manage your winners.\n",
"they reach that target, even if itís just a few days after youíve placed the trade. If you get\n",
"Letís open up Nvidia, symbol NVDA. Both of our strikes are out of the\n",
"risk of it turning downward, and we could lose out on some gains. Since weíve already\n",
"achieved 98% of our max gain, Iím going to close this trade to lock in that profit.\n",
"To close the position Iíll click the symbol, which opens up more details.\n",
"So you can see Iím selling the long put and buying the short put for a debit of\n",
"8 cents. Iím going to nudge that to 9 cents to increase my likelihood of getting filled.\n",
"Now Iím going to click review, where I can see the cost of the trade, which includes $1.30 in fees.\n",
"Ok, letís go back to our positions and take a look at another one. Iíve got a spread on Union\n",
"But Iíll give it one more day in hopes itíll turn around and I can avoid max loss. Remember,\n",
"In any event Iíll close it tomorrow, whether weíre further from max loss or closer to it,\n",
"Alright, letís look at one more sample trade to answer the question, What happens if the stock\n",
"12 137. Iíve only got 2 days to expiration, and the stock is now just above 137, so the short put\n",
"is in the money, but the long put hasnít been hit yet. Weíre facing a potentially tricky scenario.\n",
"I havenít hit max loss yet, but Iím definitely at risk of assignment on the short put and my\n",
"never intended to own. So, to avoid assignment, Iím going to close the position for a loss.\n",
"Iíll follow the same process as my earlier trade that was a winner: click the symbol,\n",
"click close selected. Iím going to leave it at the mid price and review the details, which show Iím\n",
"so Iím preventing a max loss. Note the transaction fee of $1.30. Now Iíll click send.\n",
"There you go. Thatís the nuts and bolts of the short put vertical.\n",
"and less risky than others youíve seen out there, itís still risky. Make sure\n",
"which weíve linked to in the description. We have a ton of other education on our channel,\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\n"
]
}
],
"source": [
"with open(\"/data/suno/data/harvest/youtube_med/05_audio_metas_post_transcribe_2.jsonl\") as f:\n",
" for n, line in enumerate(tqdm.tqdm(f, total=148_386)):\n",
" line = line.strip()\n",
" if len(line) == 0:\n",
" continue\n",
" m = json.loads(line)\n",
" if m is None:\n",
" continue\n",
" text = \" \".join([e for _, e in m[\"timed_lines\"]])\n",
" if n > 2200 and \"í\" in text:\n",
" print(m[\"id\"])\n",
" for _, e in m[\"timed_lines\"]:\n",
" if \"í\" in e:\n",
" print(e)\n",
" break"
]
},
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"id": "ef1a1295",
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"source": []
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{
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"id": "e655891d",
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