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{
"cells": [
{
"cell_type": "code",
"execution_count": 2,
"id": "5920c653-448e-43b3-93eb-12d7073ad352",
"metadata": {
"tags": []
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/opt/espnet/tools/anaconda/envs/espnet/lib/python3.9/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
" from .autonotebook import tqdm as notebook_tqdm\n",
"[nltk_data] Downloading package averaged_perceptron_tagger to\n",
"[nltk_data] /root/nltk_data...\n",
"[nltk_data] Unzipping taggers/averaged_perceptron_tagger.zip.\n",
"[nltk_data] Downloading package cmudict to /root/nltk_data...\n",
"[nltk_data] Unzipping corpora/cmudict.zip.\n"
]
}
],
"source": [
"from espnet2.bin.asr_inference import Speech2Text"
]
},
{
"cell_type": "markdown",
"id": "32eb58d1-5edd-4cc1-9585-daa7f16efd05",
"metadata": {},
"source": [
"## Load model"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "5e4670d6-0949-48cf-b6b1-d9cc4cf3ad65",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"speech2text = Speech2Text(\"exp/config.yaml\", \"exp/valid.acc.ave_10best.pth\")"
]
},
{
"cell_type": "markdown",
"id": "3192656d-6dce-4973-a649-f7ab0c72c386",
"metadata": {
"tags": []
},
"source": [
"## Load example audiofile to transcribe"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "e8120e8e-3718-4a1a-ab7a-46ef98a6bc11",
"metadata": {
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"mina tahaksin homme täna ja homme kui saanud on kui krampsumas ise veiki panna\n"
]
}
],
"source": [
"import soundfile\n",
"speech, rate = soundfile.read(\"example_audio/emt16k.wav\")\n",
"assert rate == 16000\n",
"text, *_ = speech2text(speech)\n",
"print(text[0])"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "7cb79f15-3091-446f-9e22-e0eae96e278e",
"metadata": {
"tags": []
},
"outputs": [
{
"data": {
"text/plain": [
"('mina tahaksin homme täna ja homme kui saanud on kui krampsumas ise veiki panna',\n",
" ['▁mina',\n",
" '▁tahaksin',\n",
" '▁homme',\n",
" '▁täna',\n",
" '▁ja',\n",
" '▁homme',\n",
" '▁kui',\n",
" '▁saanud',\n",
" '▁on',\n",
" '▁kui',\n",
" '▁kra',\n",
" 'm',\n",
" 'psu',\n",
" 'mas',\n",
" '▁ise',\n",
" '▁ve',\n",
" 'i',\n",
" 'ki',\n",
" '▁panna'],\n",
" [160,\n",
" 2003,\n",
" 1403,\n",
" 101,\n",
" 4,\n",
" 1403,\n",
" 13,\n",
" 303,\n",
" 3,\n",
" 13,\n",
" 2652,\n",
" 60,\n",
" 2940,\n",
" 410,\n",
" 143,\n",
" 376,\n",
" 15,\n",
" 88,\n",
" 467],\n",
" Hypothesis(yseq=tensor([4999, 160, 2003, 1403, 101, 4, 1403, 13, 303, 3, 13, 2652,\n",
" 60, 2940, 410, 143, 376, 15, 88, 467, 4999]), score=tensor(-11.9828), scores={'decoder': tensor(-14.2027), 'ctc': tensor(-9.7630)}, states={'decoder': [tensor([[ -5.1263, 3.1550, -2.0594, ..., 24.0211, 0.3968, -0.0377],\n",
" [ -6.2288, 3.8375, 1.5658, ..., 1.4794, -19.9161, -9.2051],\n",
" [ -0.8955, -12.1962, 11.2881, ..., 14.5357, 2.5597, 5.0430],\n",
" ...,\n",
" [ -1.5868, 0.9150, 7.6028, ..., 6.9893, -9.0237, -6.0684],\n",
" [ -0.2270, -5.4793, -4.3761, ..., 8.3707, 3.3640, -10.0500],\n",
" [ -3.5901, 5.2413, -6.3700, ..., 1.8956, -1.3764, 2.8161]]), tensor([[ -3.6827, 2.9746, -2.4586, ..., 21.4053, 0.7093, 0.0590],\n",
" [ -3.6746, 2.3007, 6.9940, ..., 0.4042, -26.4674, -7.6587],\n",
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" ...,\n",
" [ -3.0836, 8.8793, 15.3461, ..., 6.7483, -10.2614, -12.3279],\n",
" [ -3.0388, -4.8860, 1.2961, ..., 7.1166, 7.1762, -11.6877],\n",
" [ -6.3154, 10.7874, -8.3653, ..., -2.7268, 6.2414, 2.0028]]), tensor([[ -4.2097, 3.3128, -4.3004, ..., 19.7619, 0.0523, 0.5325],\n",
" [ -2.0206, 5.0642, 3.8430, ..., 4.3120, -31.3507, -4.5523],\n",
" [ -4.9023, -11.4819, 30.5385, ..., 23.1088, 7.1218, 6.8997],\n",
" ...,\n",
" [ -7.4921, 14.9905, 18.8936, ..., 14.4608, -14.1381, -20.3670],\n",
" [ -7.2482, -3.5175, -1.7658, ..., 13.9724, 3.8404, -19.6644],\n",
" [ -4.5970, 14.7940, 1.5388, ..., -3.3481, 2.3485, 1.7171]]), tensor([[ -2.6693, 5.9532, -6.0862, ..., 18.1037, 1.8700, 1.8734],\n",
" [ -3.4684, 1.5924, -2.2865, ..., 17.7742, -34.5136, -5.1747],\n",
" [-14.9132, -16.1804, 39.0452, ..., 19.7372, 15.8912, 11.7538],\n",
" ...,\n",
" [-13.3347, 13.1394, 22.9955, ..., 15.1552, -26.7795, -35.4029],\n",
" [-20.9897, -12.5458, 2.4344, ..., 25.7768, 4.4565, -20.4715],\n",
" [-11.9333, 21.3926, 0.9612, ..., -7.3184, 1.1050, -8.7355]]), tensor([[ -8.3364, -8.5930, 12.5300, ..., 14.0010, 9.2563, 15.4071],\n",
" [-11.7589, -8.5604, -14.7583, ..., 27.1039, -22.6838, 8.2407],\n",
" [-26.8291, -28.9856, 66.4735, ..., 10.2667, 51.7921, 13.9935],\n",
" ...,\n",
" [-24.8075, 8.7724, 35.3504, ..., -15.1498, -51.6167, -44.5583],\n",
" [-25.6442, -8.3698, 14.0967, ..., 21.2507, 16.2526, -28.0444],\n",
" [ -9.2648, 33.3486, 10.6099, ..., -8.6877, 0.9520, -13.3015]]), tensor([[-30.5616, -7.4708, 56.1848, ..., 1.5934, 20.7831, 44.0383],\n",
" [-51.2013, 29.8913, -73.0093, ..., -2.1801, -11.0278, 151.5184],\n",
" [-74.1030, -51.1745, 158.5696, ..., 40.8046, 92.3456, 42.8557],\n",
" ...,\n",
" [-56.5551, 4.2527, 102.6477, ..., 4.8044, -99.0702, -65.3296],\n",
" [-22.1416, 8.2998, 48.0735, ..., -36.2092, 40.0850, 6.7160],\n",
" [-21.1855, 35.3772, -11.6307, ..., 17.0477, 6.7013, -32.2759]])], 'ctc': (tensor([[-1.0000e+10, -1.0000e+10],\n",
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]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"text"
]
},
{
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"execution_count": null,
"id": "e03dcce0-e322-465f-b1d1-c266dec80b6b",
"metadata": {},
"outputs": [],
"source": []
}
],
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|