{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"executionInfo": {
"elapsed": 829,
"status": "ok",
"timestamp": 1641588786523,
"user": {
"displayName": "Yurii Paniv",
"photoUrl": "https://lh3.googleusercontent.com/a/default-user=s64",
"userId": "13095662915325887123"
},
"user_tz": -120
},
"id": "YELVqGxMxnbG",
"outputId": "876761c1-2e03-411b-e61b-07ac4ad61377"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Mon Dec 26 17:51:09 2022 \n",
"+-----------------------------------------------------------------------------+\n",
"| NVIDIA-SMI 515.86.01 Driver Version: 515.86.01 CUDA Version: 11.7 |\n",
"|-------------------------------+----------------------+----------------------+\n",
"| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |\n",
"| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |\n",
"| | | MIG M. |\n",
"|===============================+======================+======================|\n",
"| 0 NVIDIA GeForce ... Off | 00000000:0A:00.0 On | N/A |\n",
"| 0% 34C P5 49W / 390W | 1437MiB / 24576MiB | 2% Default |\n",
"| | | N/A |\n",
"+-------------------------------+----------------------+----------------------+\n",
" \n",
"+-----------------------------------------------------------------------------+\n",
"| Processes: |\n",
"| GPU GI CI PID Type Process name GPU Memory |\n",
"| ID ID Usage |\n",
"|=============================================================================|\n",
"| 0 N/A N/A 1223 G /usr/lib/xorg/Xorg 498MiB |\n",
"| 0 N/A N/A 2007 G /usr/bin/kwalletd5 4MiB |\n",
"| 0 N/A N/A 2174 G ...ec/xdg-desktop-portal-kde 4MiB |\n",
"| 0 N/A N/A 2211 G /usr/bin/ksmserver 4MiB |\n",
"| 0 N/A N/A 2213 G /usr/bin/kded5 4MiB |\n",
"| 0 N/A N/A 2214 G /usr/bin/kwin_x11 96MiB |\n",
"| 0 N/A N/A 2263 G /usr/bin/plasmashell 96MiB |\n",
"| 0 N/A N/A 2283 G ...de-authentication-agent-1 4MiB |\n",
"| 0 N/A N/A 2354 G ...x-gnu/libexec/kdeconnectd 4MiB |\n",
"| 0 N/A N/A 2356 G .../usr/bin/telegram-desktop 7MiB |\n",
"| 0 N/A N/A 2370 G /usr/bin/kaccess 4MiB |\n",
"| 0 N/A N/A 2377 G .../libexec/DiscoverNotifier 4MiB |\n",
"| 0 N/A N/A 2443 G ...1/usr/lib/firefox/firefox 96MiB |\n",
"| 0 N/A N/A 2704 G /usr/bin/dolphin 4MiB |\n",
"| 0 N/A N/A 2806 G /usr/bin/dolphin 4MiB |\n",
"| 0 N/A N/A 2911 G /usr/bin/dolphin 4MiB |\n",
"| 0 N/A N/A 6634 G ...RendererForSitePerProcess 585MiB |\n",
"+-----------------------------------------------------------------------------+\n"
]
}
],
"source": [
"gpu_info = !nvidia-smi\n",
"gpu_info = '\\n'.join(gpu_info)\n",
"if gpu_info.find('failed') >= 0:\n",
" print('Not connected to a GPU')\n",
"else:\n",
" print(gpu_info)"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"id": "c8eh87Hoee5d"
},
"outputs": [],
"source": [
"#%%capture\n",
"#!pip install datasets==1.13.3\n",
"#!pip install transformers==4.11.3\n",
"#!pip install huggingface_hub==0.1\n",
"#!pip install torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html\n",
"#!pip install jiwer"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"executionInfo": {
"elapsed": 5334,
"status": "ok",
"timestamp": 1641588811766,
"user": {
"displayName": "Yurii Paniv",
"photoUrl": "https://lh3.googleusercontent.com/a/default-user=s64",
"userId": "13095662915325887123"
},
"user_tz": -120
},
"id": "2MMXcWFFgCXU",
"outputId": "be9fd72e-4395-4cd0-ff87-631dad046e71"
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"Reusing dataset common_voice_10_0 (/home/robinhad/.cache/huggingface/datasets/mozilla-foundation___common_voice_10_0/uk/10.0.0/27df768ab1b5cac48a7616f145b79b62599167b0ffa2e054bf4c3e74e9619e5e)\n",
"Reusing dataset common_voice_10_0 (/home/robinhad/.cache/huggingface/datasets/mozilla-foundation___common_voice_10_0/uk/10.0.0/27df768ab1b5cac48a7616f145b79b62599167b0ffa2e054bf4c3e74e9619e5e)\n"
]
}
],
"source": [
"from datasets import load_dataset, load_metric, Audio\n",
"\n",
"common_voice_train = load_dataset(\"mozilla-foundation/common_voice_10_0\", \"uk\", split=\"train\", use_auth_token=True)\n",
"common_voice_test = load_dataset(\"mozilla-foundation/common_voice_10_0\", \"uk\", split=\"test\", use_auth_token=True)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Dataset({\n",
" features: ['client_id', 'path', 'audio', 'sentence', 'up_votes', 'down_votes', 'age', 'gender', 'accent', 'locale', 'segment'],\n",
" num_rows: 11463\n",
"})"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"common_voice_train"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"common_voice_train.cleanup_cache_files()\n",
"common_voice_test.cleanup_cache_files()"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"id": "kbyq6lDgQc2a"
},
"outputs": [],
"source": [
"common_voice_train = common_voice_train.remove_columns([\"accent\", \"age\", \"client_id\", \"down_votes\", \"gender\", \"locale\", \"segment\", \"up_votes\"])\n",
"common_voice_test = common_voice_test.remove_columns([\"accent\", \"age\", \"client_id\", \"down_votes\", \"gender\", \"locale\", \"segment\", \"up_votes\"])"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"id": "72737oog2F6U"
},
"outputs": [],
"source": [
"from datasets import ClassLabel\n",
"import random\n",
"import pandas as pd\n",
"from IPython.display import display, HTML\n",
"\n",
"def show_random_elements(dataset, num_examples=10):\n",
" assert num_examples <= len(dataset), \"Can't pick more elements than there are in the dataset.\"\n",
" picks = []\n",
" for _ in range(num_examples):\n",
" pick = random.randint(0, len(dataset)-1)\n",
" while pick in picks:\n",
" pick = random.randint(0, len(dataset)-1)\n",
" picks.append(pick)\n",
" \n",
" df = pd.DataFrame(dataset[picks])\n",
" display(HTML(df.to_html()))"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 363
},
"executionInfo": {
"elapsed": 39,
"status": "ok",
"timestamp": 1641588811771,
"user": {
"displayName": "Yurii Paniv",
"photoUrl": "https://lh3.googleusercontent.com/a/default-user=s64",
"userId": "13095662915325887123"
},
"user_tz": -120
},
"id": "K_JUmf3G3b9S",
"outputId": "8603c909-09e1-43ae-f7c2-b27b25d795a3"
},
"outputs": [
{
"data": {
"text/html": [
"
\n",
" \n",
" \n",
" | \n",
" sentence | \n",
"
\n",
" \n",
" \n",
" \n",
" 0 | \n",
" Щоночі одна півсотня ночувала у лісі, друга — в селі. | \n",
"
\n",
" \n",
" 1 | \n",
" І зараз за тим днем твоя доля зміниться на краще. | \n",
"
\n",
" \n",
" 2 | \n",
" Оп'ять Ірисю посила: | \n",
"
\n",
" \n",
" 3 | \n",
" Рушниця впала по той бік плоту. | \n",
"
\n",
" \n",
" 4 | \n",
" Загуде вона, як гром. | \n",
"
\n",
" \n",
" 5 | \n",
" Дружина не витримує і сміється. | \n",
"
\n",
" \n",
" 6 | \n",
" Люблю, тільки боюся говорити. | \n",
"
\n",
" \n",
" 7 | \n",
" Звір заревів востаннє, сіпнувся головою назад і зник під водою. | \n",
"
\n",
" \n",
" 8 | \n",
" Про їзду риссю не могло бути й мови. | \n",
"
\n",
" \n",
" 9 | \n",
" Ми заночували в Бондуровій, — червоні — в Баландиному. | \n",
"
\n",
" \n",
"
"
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"show_random_elements(common_voice_train.remove_columns([\"path\", \"audio\"]), num_examples=10)"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"executionInfo": {
"elapsed": 30,
"status": "ok",
"timestamp": 1641588811775,
"user": {
"displayName": "Yurii Paniv",
"photoUrl": "https://lh3.googleusercontent.com/a/default-user=s64",
"userId": "13095662915325887123"
},
"user_tz": -120
},
"id": "XIHocAuTQbBR",
"outputId": "e8392853-e0d1-45ba-df74-065c50565654"
},
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],
"source": [
"filter_func = lambda x: not (\"joki\" in x or \"ы\" in x)\n",
"common_voice_train = common_voice_train.filter(filter_func, input_columns=[\"sentence\"])\n",
"common_voice_test = common_voice_test.filter(filter_func, input_columns=[\"sentence\"])"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"id": "ZcVsD0ETElrR"
},
"outputs": [
{
"data": {
"text/plain": [
"{'sentence': \"привіт як у тебе справи загалом м'якотілий друже\"}"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"def cleaner(batch):\n",
" replace_as_space = \"!:;,—…–“”?\\\"«»\"\n",
" special_words = {\n",
" \"ХIХ\": \"дев'ятнадцятого\",\n",
" \"Linux\": \"Лінукс\",\n",
" \"Maace\": \"Маасе\",\n",
" \"м 'ясо\": \"м'ясо\",\n",
" \"'іде\": \"іде\",\n",
" \"Д'Аламбер\": \"даламбер\",\n",
" \" - \": \" \",\n",
" \"--\": \" \",\n",
" \"....\": \" \",\n",
" \"...\": \" \",\n",
" \"..\": \" \",\n",
" \" '\": \" \",\n",
" \"О'\": \"о\",\n",
" \"-\": \"\" #further check needed\n",
" }\n",
" # check abbreviations later\n",
" abbreviations = {\n",
" 'ЧК': \"чека\",\n",
" 'ҐПУ': \"ґепеу\",\n",
" 'ЄС.': \"єес\",\n",
" 'УНР': \"уенер\",\n",
" 'ДТП.': \"детепе\",\n",
" 'РНБО': \"еренбео\",\n",
" 'СРСР': \"есересер\",\n",
" 'ДБР': \"дебеер\",\n",
" 'КП': \"капе\",\n",
" 'ОС': \"оес\",\n",
" } \n",
" chars_dict = {\n",
" \"C\": \"С\",\n",
" \"I\": \"І\",\n",
" \"P\": \"Р\",\n",
" \"a\": \"а\",\n",
" \"e\": \"е\",\n",
" \"x\": \"х\",\n",
" \"y\": \"у\",\n",
" \"p\": \"р\",\n",
" \"o\": \"о\",\n",
" \"i\": \"і\",\n",
" \"\\u0301\": \"\",\n",
" \"`\": \"'\",\n",
" \"՚\": \"'\",\n",
" \".\": \" \",\n",
" \"’\": \"'\"\n",
" \n",
" }\n",
" for word in special_words.keys():\n",
" batch[\"sentence\"] = batch[\"sentence\"].replace(word, special_words[word])\n",
" for word in abbreviations.keys():\n",
" batch[\"sentence\"] = batch[\"sentence\"].replace(word, abbreviations[word])\n",
" for char in chars_dict.keys():\n",
" batch[\"sentence\"] = batch[\"sentence\"].replace(char, chars_dict[char])\n",
" for char in replace_as_space:\n",
" batch[\"sentence\"] = batch[\"sentence\"].replace(char, \" \")\n",
" batch[\"sentence\"] = \" \".join(filter(lambda x: x != \"\", batch[\"sentence\"].strip().lower().split(\" \")))\n",
" return batch\n",
"\n",
"sentence = {\"sentence\": \"Привіт, - як у тебе справи загалом, м'якотілий друже?\"}\n",
"cleaner(sentence)"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 401
},
"executionInfo": {
"elapsed": 32,
"status": "ok",
"timestamp": 1641588811774,
"user": {
"displayName": "Yurii Paniv",
"photoUrl": "https://lh3.googleusercontent.com/a/default-user=s64",
"userId": "13095662915325887123"
},
"user_tz": -120
},
"id": "6falIJSBED65",
"outputId": "2f0ca829-dbfa-4d70-ee4a-ded2ae342117"
},
"outputs": [
{
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{
"data": {
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"\n",
" \n",
" \n",
" | \n",
" sentence | \n",
"
\n",
" \n",
" \n",
" \n",
" 0 | \n",
" простіть | \n",
"
\n",
" \n",
" 1 | \n",
" полковник дасть вам проїзні документи до табору | \n",
"
\n",
" \n",
" 2 | \n",
" зараз тільки про це йде мова | \n",
"
\n",
" \n",
" 3 | \n",
" у мене лопата вартий на килимі до кам'янки вернутися | \n",
"
\n",
" \n",
" 4 | \n",
" хотілося взнати про холодний яр про долю товаришів | \n",
"
\n",
" \n",
" 5 | \n",
" а той слухає уважно перепитує | \n",
"
\n",
" \n",
" 6 | \n",
" чи то образ перемінився в чоловіка чи чоловік був у тім образі | \n",
"
\n",
" \n",
" 7 | \n",
" кінь | \n",
"
\n",
" \n",
" 8 | \n",
" у самців вусики трохи довші а у самок дещо коротші за тіло | \n",
"
\n",
" \n",
" 9 | \n",
" чорний туман що сповивав усе довкола поволі сірів | \n",
"
\n",
" \n",
"
"
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"show_random_elements(common_voice_train.map(cleaner).remove_columns([\"path\", \"audio\"]), num_examples=10)"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"Loading cached processed dataset at /home/robinhad/.cache/huggingface/datasets/mozilla-foundation___common_voice_10_0/uk/10.0.0/27df768ab1b5cac48a7616f145b79b62599167b0ffa2e054bf4c3e74e9619e5e/cache-890587fbc5f83609.arrow\n"
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"version_minor": 0
},
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" 0%| | 0/6783 [00:00, ?ex/s]"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"common_voice_train = common_voice_train.map(cleaner)\n",
"common_voice_test = common_voice_test.map(cleaner)"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 363
},
"executionInfo": {
"elapsed": 24,
"status": "ok",
"timestamp": 1641588811775,
"user": {
"displayName": "Yurii Paniv",
"photoUrl": "https://lh3.googleusercontent.com/a/default-user=s64",
"userId": "13095662915325887123"
},
"user_tz": -120
},
"id": "RBDRAAYxRE6n",
"outputId": "a16beae1-84e6-4388-d601-2ed3a92bf451"
},
"outputs": [
{
"data": {
"text/html": [
"\n",
" \n",
" \n",
" | \n",
" sentence | \n",
"
\n",
" \n",
" \n",
" \n",
" 0 | \n",
" спостерігаючи за їхніми спокійними рухами пригадую роботу чекістів у льоху для розстрілів | \n",
"
\n",
" \n",
" 1 | \n",
" сірого били дрючками селяни що упіймали його з парою крадених коней | \n",
"
\n",
" \n",
" 2 | \n",
" мав лише револьвер далековид і планшет із мапою | \n",
"
\n",
" \n",
" 3 | \n",
" коли еней мене бажа | \n",
"
\n",
" \n",
" 4 | \n",
" ось і волость | \n",
"
\n",
" \n",
" 5 | \n",
" і посмоктали кісточки | \n",
"
\n",
" \n",
" 6 | \n",
" скакати високо | \n",
"
\n",
" \n",
" 7 | \n",
" я стрепенувся і відкрив повіки | \n",
"
\n",
" \n",
" 8 | \n",
" нападом на кінноту ми себе виявили | \n",
"
\n",
" \n",
" 9 | \n",
" червоні розгубилися і в безладі закрутилися на місці | \n",
"
\n",
" \n",
"
"
],
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]
},
"metadata": {},
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}
],
"source": [
"show_random_elements(common_voice_train.remove_columns([\"path\",\"audio\"]))"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {
"id": "LwCshNbbeRZR"
},
"outputs": [],
"source": [
"def extract_all_chars(batch):\n",
" all_text = \" \".join(batch[\"sentence\"])\n",
" vocab = list(set(all_text))\n",
" return {\"vocab\": [vocab], \"all_text\": [all_text]}"
]
},
{
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],
"source": [
"vocab_train = common_voice_train.map(extract_all_chars, batched=True, batch_size=-1, keep_in_memory=True, remove_columns=common_voice_train.column_names)\n",
"vocab_test = common_voice_test.map(extract_all_chars, batched=True, batch_size=-1, keep_in_memory=True, remove_columns=common_voice_test.column_names)"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {
"id": "aQfneNsmlJI0"
},
"outputs": [],
"source": [
"vocab_list = list(set(vocab_train[\"vocab\"][0]) | set(vocab_test[\"vocab\"][0]))"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"executionInfo": {
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"status": "ok",
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"user_tz": -120
},
"id": "_0kRndSvqaKk",
"outputId": "35c48e76-5060-470b-8405-bd6d288296ea"
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{
"data": {
"text/plain": [
"{' ': 0,\n",
" \"'\": 1,\n",
" 'а': 2,\n",
" 'б': 3,\n",
" 'в': 4,\n",
" 'г': 5,\n",
" 'д': 6,\n",
" 'е': 7,\n",
" 'ж': 8,\n",
" 'з': 9,\n",
" 'и': 10,\n",
" 'й': 11,\n",
" 'к': 12,\n",
" 'л': 13,\n",
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" 'н': 15,\n",
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" 'п': 17,\n",
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" 'ґ': 34}"
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},
"execution_count": 19,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"vocab_dict = {v: k for k, v in enumerate(sorted(vocab_list))}\n",
"vocab_dict"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {
"id": "npbIbBoLgaFX"
},
"outputs": [],
"source": [
"vocab_dict[\"|\"] = vocab_dict[\" \"]\n",
"del vocab_dict[\" \"]"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"executionInfo": {
"elapsed": 15,
"status": "ok",
"timestamp": 1641588812316,
"user": {
"displayName": "Yurii Paniv",
"photoUrl": "https://lh3.googleusercontent.com/a/default-user=s64",
"userId": "13095662915325887123"
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"id": "znF0bNunsjbl",
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"outputs": [
{
"data": {
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"37"
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"vocab_dict[\"[UNK]\"] = len(vocab_dict)\n",
"vocab_dict[\"[PAD]\"] = len(vocab_dict)\n",
"len(vocab_dict)"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {
"id": "ehyUoh9vk191"
},
"outputs": [],
"source": [
"import json\n",
"with open('vocab.json', 'w') as vocab_file:\n",
" json.dump(vocab_dict, vocab_file)"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"executionInfo": {
"elapsed": 8013,
"status": "ok",
"timestamp": 1641588820318,
"user": {
"displayName": "Yurii Paniv",
"photoUrl": "https://lh3.googleusercontent.com/a/default-user=s64",
"userId": "13095662915325887123"
},
"user_tz": -120
},
"id": "xriFGEWQkO4M",
"outputId": "a4497f75-d6f5-411a-d983-2ad519f65b8b"
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n"
]
}
],
"source": [
"from transformers import Wav2Vec2CTCTokenizer\n",
"\n",
"tokenizer = Wav2Vec2CTCTokenizer.from_pretrained(\"./\", unk_token=\"[UNK]\", pad_token=\"[PAD]\", word_delimiter_token=\"|\")"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {
"id": "A1XApZBAF2zr"
},
"outputs": [],
"source": [
"repo_name = \"wav2vec2-xls-r-base-uk\""
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {
"id": "kAR0-2KLkopp"
},
"outputs": [],
"source": [
"from transformers import Wav2Vec2FeatureExtractor\n",
"\n",
"feature_extractor = Wav2Vec2FeatureExtractor(feature_size=1, sampling_rate=16000, padding_value=0.0, do_normalize=True, return_attention_mask=True)"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {
"id": "KYZtoW-tlZgl"
},
"outputs": [],
"source": [
"from transformers import Wav2Vec2Processor\n",
"\n",
"processor = Wav2Vec2Processor(feature_extractor=feature_extractor, tokenizer=tokenizer)"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {},
"outputs": [],
"source": [
"# save tokenizer to folder\n",
"processor.save_pretrained(repo_name)"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 54
},
"executionInfo": {
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"status": "ok",
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},
"id": "TTCS7W6XJ9BG",
"outputId": "18b0d44f-a498-4a79-f0a7-984fae48cad1"
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"outputs": [
{
"data": {
"text/plain": [
"'/home/robinhad/.cache/huggingface/datasets/downloads/extracted/ee7155196e5d51620d53e48cf58eb693b7839b8ff183604c8bb948d3e0aad92d/cv-corpus-10.0-2022-07-04/uk/clips/common_voice_uk_20907128.mp3'"
]
},
"execution_count": 29,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"common_voice_train[0][\"path\"]"
]
},
{
"cell_type": "code",
"execution_count": 30,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"executionInfo": {
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"status": "ok",
"timestamp": 1641588821172,
"user": {
"displayName": "Yurii Paniv",
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},
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},
"id": "qj_z5Zc3GAs9",
"outputId": "ace70f42-dcf0-445c-9b81-b23d4089c90d"
},
"outputs": [
{
"data": {
"text/plain": [
"{'path': '/home/robinhad/.cache/huggingface/datasets/downloads/extracted/ee7155196e5d51620d53e48cf58eb693b7839b8ff183604c8bb948d3e0aad92d/cv-corpus-10.0-2022-07-04/uk/clips/common_voice_uk_20907128.mp3',\n",
" 'array': array([ 0.0000000e+00, -3.5002383e-14, 9.4785833e-15, ...,\n",
" -5.0386465e-08, -4.4114326e-08, -1.9402206e-08], dtype=float32),\n",
" 'sampling_rate': 48000}"
]
},
"execution_count": 30,
"metadata": {},
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}
],
"source": [
"common_voice_train[0][\"audio\"]"
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {
"id": "rrv65aj7G95i"
},
"outputs": [],
"source": [
"common_voice_train = common_voice_train.cast_column(\"audio\", Audio(sampling_rate=16_000))\n",
"common_voice_test = common_voice_test.cast_column(\"audio\", Audio(sampling_rate=16_000))"
]
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {
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},
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},
"id": "aKtkc1o_HWHC",
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"metadata": {},
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}
],
"source": [
"common_voice_train[0][\"audio\"]"
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 80
},
"executionInfo": {
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"status": "ok",
"timestamp": 1641588821175,
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},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"що ж хоч утекти можна вкупі з нею\n"
]
},
{
"data": {
"text/html": [
"\n",
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 33,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import IPython.display as ipd\n",
"import numpy as np\n",
"import random\n",
"\n",
"rand_int = random.randint(0, len(common_voice_train)-1)\n",
"\n",
"print(common_voice_train[rand_int][\"sentence\"])\n",
"ipd.Audio(data=common_voice_train[rand_int][\"audio\"][\"array\"], autoplay=True, rate=16000)"
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"executionInfo": {
"elapsed": 22,
"status": "ok",
"timestamp": 1641588821176,
"user": {
"displayName": "Yurii Paniv",
"photoUrl": "https://lh3.googleusercontent.com/a/default-user=s64",
"userId": "13095662915325887123"
},
"user_tz": -120
},
"id": "1Po2g7YPuRTx",
"outputId": "ad79ec8a-ab5a-4c52-edfa-a20d0eec2282"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Target text: троє\n",
"Input array shape: (26496,)\n",
"Sampling rate: 16000\n"
]
}
],
"source": [
"rand_int = random.randint(0, len(common_voice_train)-1)\n",
"\n",
"print(\"Target text:\", common_voice_train[rand_int][\"sentence\"])\n",
"print(\"Input array shape:\", common_voice_train[rand_int][\"audio\"][\"array\"].shape)\n",
"print(\"Sampling rate:\", common_voice_train[rand_int][\"audio\"][\"sampling_rate\"])"
]
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {
"id": "eJY7I0XAwe9p"
},
"outputs": [],
"source": [
"def prepare_dataset(batch):\n",
" audio = batch[\"audio\"]\n",
"\n",
" # batched output is \"un-batched\"\n",
" batch[\"input_values\"] = processor(audio[\"array\"], sampling_rate=audio[\"sampling_rate\"]).input_values[0]\n",
" batch[\"input_length\"] = len(batch[\"input_values\"])\n",
" \n",
" with processor.as_target_processor():\n",
" batch[\"labels\"] = processor(batch[\"sentence\"]).input_ids\n",
" return batch"
]
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {
"colab": {
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"height": 87,
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],
"source": [
"common_voice_train = common_voice_train.map(prepare_dataset, remove_columns=common_voice_train.column_names)\n",
"common_voice_test = common_voice_test.map(prepare_dataset, remove_columns=common_voice_test.column_names)"
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {
"id": "tdHfbUJ_09iA"
},
"outputs": [],
"source": [
"#max_input_length_in_sec = 5.0\n",
"#common_voice_train = common_voice_train.filter(lambda x: x < max_input_length_in_sec * processor.feature_extractor.sampling_rate, input_columns=[\"input_length\"])"
]
},
{
"cell_type": "code",
"execution_count": 37,
"metadata": {},
"outputs": [],
"source": [
"!mkdir cached_dataset"
]
},
{
"cell_type": "code",
"execution_count": 38,
"metadata": {},
"outputs": [],
"source": [
"common_voice_train.save_to_disk(\"cached_dataset/cv_train\")"
]
},
{
"cell_type": "code",
"execution_count": 39,
"metadata": {},
"outputs": [],
"source": [
"common_voice_test.save_to_disk(\"cached_dataset/cv_test\")"
]
}
],
"metadata": {
"accelerator": "GPU",
"colab": {
"collapsed_sections": [],
"machine_shape": "hm",
"name": "Копія записника \"Fine-Tune XLS-R on Common Voice.ipynb\"",
"provenance": [
{
"file_id": "https://github.com/patrickvonplaten/notebooks/blob/master/Fine_Tune_XLS_R_on_Common_Voice.ipynb",
"timestamp": 1641583715050
}
]
},
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"language": "python",
"name": "python3"
},
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"file_extension": ".py",
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