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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "71d69be2",
"metadata": {},
"outputs": [],
"source": [
"import torchaudio\n",
"import numpy as np \n",
"import torch\n",
"import pandas as pd\n",
"import os"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "eb5c6da2",
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"text/plain": [
"['Salah1.wav',\n",
" 'Salah2.wav',\n",
" 'Salah3.wav',\n",
" 'Salah4.wav',\n",
" 'Salah5.wav',\n",
" 'Salah6.wav',\n",
" 'Salah7.wav',\n",
" 'Salah8.wav',\n",
" 'Salah9.wav',\n",
" 'Salah10.wav']"
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"files = os.listdir(\"./\")\n",
"files = [x for x in files if \".wav\" in x]\n",
"files = [f\"Salah{i}.wav\" for i in range(1,11)]\n",
"files"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "b2be1d8e",
"metadata": {},
"outputs": [],
"source": [
"words = {}\n",
"words[1] = \"نحب ماكلة بنينة كسكروت نظيف و رخيص\"\n",
"words[2]= \"باهي وقتاش نمشيو ال تونس\"\n",
"words[3] = \"اعطيني خمسة الاف و خمسة ميا بلاهي\"\n",
"words[4] = \"تعبت هاني راكش في الدار\"\n",
"words[5] = \"نهار السبت ماشي نقرى ان شاء الله\"\n",
"words[6]= \"زعما نلقى أحمد في الستاد ولا ماهوش هوني\"\n",
"words[7]= \"نحب نمشي ال بنزرت نرتاح شوية\"\n",
"words[8] = \"حكيت مع لولاد قالولي كل شي مريقل نهار السبت\"\n",
"words[9] = \"ناكل كفتاجي و نجم نشري شوية حوت زادة\"\n",
"words[10] = \"انتي خويا و عشيري صالح نحبك\"\n",
"words = [words[i] for i in range(1,11)]"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "c46588ba",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"torch.Size([1, 238080])\n",
"torch.Size([1, 184320])\n",
"torch.Size([1, 207360])\n",
"torch.Size([1, 168960])\n",
"torch.Size([1, 168960])\n",
"torch.Size([1, 192000])\n",
"torch.Size([1, 184320])\n",
"torch.Size([1, 199680])\n",
"torch.Size([1, 230400])\n",
"torch.Size([1, 192000])\n"
]
}
],
"source": [
"durations= []\n",
"path_jz = \"samples/\"\n",
"paths = [os.path.join(path_jz,x) for x in files]\n",
"srs= [48000 for x in paths]\n",
"IDs=[]\n",
"for f in files: \n",
" x,sr = torchaudio.load(f)\n",
" new_audio = torch.mean(x, dim=0).unsqueeze(0)\n",
" print(new_audio.shape)\n",
" torchaudio.save(os.path.join(\"monoaudiotun\", f), new_audio, sr)\n",
" duration = float(x.shape[1]) / sr\n",
" durations.append(duration)\n",
" IDs.append(f.split(\".\")[0])\n",
" \n"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "b71db098",
"metadata": {},
"outputs": [],
"source": [
"test_salah = pd.DataFrame(\n",
" {'ID': IDs,\n",
" 'duration': durations,\n",
" 'wav': paths,\n",
" \"sr\": srs,\n",
" \"wrd\": words\n",
" })\n"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "b3fdd365",
"metadata": {},
"outputs": [],
"source": [
"test_salah.to_csv(\"test_salah_local.csv\", index=False)"
]
},
{
"cell_type": "code",
"execution_count": 28,
"id": "f6ac8451",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"%WER 45.59 [ 31 / 68, 3 ins, 7 del, 21 sub ]\n",
"%SER 90.00 [ 9 / 10 ]\n",
"Scored 10 sentences, 0 not present in hyp.\n",
"================================================================================\n",
"ALIGNMENTS\n",
"\n",
"Format:\n",
"<utterance-id>, WER DETAILS\n",
"<eps> ; reference ; on ; the ; first ; line\n",
" I ; S ; = ; = ; S ; D \n",
" and ; hypothesis ; on ; the ; third ; <eps>\n",
"================================================================================\n",
"Salah4, %WER 0.00 [ 0 / 5, 0 ins, 0 del, 0 sub ]\n",
"تعبت ; هاني ; راكش ; في ; الدار\n",
" = ; = ; = ; = ; = \n",
"تعبت ; هاني ; راكش ; في ; الدار\n",
"================================================================================\n",
"Salah5, %WER 57.14 [ 4 / 7, 0 ins, 1 del, 3 sub ]\n",
"نهار ; السبت ; ماشي ; نقرى ; ان ; شاء ; الله\n",
" = ; = ; = ; S ; S ; S ; D \n",
"نهار ; السبت ; ماشي ; نقرا ; إن ; شاءالله ; <eps>\n",
"================================================================================\n",
"Salah2, %WER 60.00 [ 3 / 5, 0 ins, 1 del, 2 sub ]\n",
"باهي ; وقتاش ; نمشيو ; ال ; تونس\n",
" = ; = ; S ; S ; D \n",
"باهي ; وقتاش ; نمشيوا ; لتونس ; <eps>\n",
"================================================================================\n",
"Salah7, %WER 33.33 [ 2 / 6, 0 ins, 1 del, 1 sub ]\n",
"نحب ; نمشي ; ال ; بنزرت ; نرتاح ; شوية\n",
" = ; = ; S ; D ; = ; = \n",
"نحب ; نمشي ; لبنزرت ; <eps> ; نرتاح ; شوية\n",
"================================================================================\n",
"Salah6, %WER 37.50 [ 3 / 8, 0 ins, 0 del, 3 sub ]\n",
"زعما ; نلقى ; أحمد ; في ; الستاد ; ولا ; ماهوش ; هوني\n",
" S ; = ; = ; = ; S ; S ; = ; = \n",
"زعمة ; نلقى ; أحمد ; في ; السعد ; وإلا ; ماهوش ; هوني\n",
"================================================================================\n",
"Salah10, %WER 83.33 [ 5 / 6, 1 ins, 1 del, 3 sub ]\n",
"انتي ; <eps> ; خويا ; و ; عشيري ; صالح ; نحبك\n",
" S ; I ; = ; S ; S ; D ; = \n",
"إنت ; ي ; خويا ; وعشيلي ; صلاح ; <eps> ; نحبك\n",
"================================================================================\n",
"Salah8, %WER 44.44 [ 4 / 9, 2 ins, 0 del, 2 sub ]\n",
"حكيت ; مع ; لولاد ; قالولي ; كل ; شي ; مريقل ; <eps> ; <eps> ; نهار ; السبت\n",
" = ; = ; S ; = ; = ; = ; S ; I ; I ; = ; = \n",
"حكيت ; مع ; الأولاد ; قالولي ; كل ; شي ; مر ; ي ; ل ; نهار ; السبت\n",
"================================================================================\n",
"Salah3, %WER 85.71 [ 6 / 7, 0 ins, 1 del, 5 sub ]\n",
"اعطيني ; خمسة ; الاف ; و ; خمسة ; ميا ; بلاهي\n",
" S ; = ; S ; S ; S ; S ; D \n",
"أعطيني ; خمسة ; آلاف ; وخمسة ; ملا ; باللاهي ; <eps>\n",
"================================================================================\n",
"Salah9, %WER 25.00 [ 2 / 8, 0 ins, 1 del, 1 sub ]\n",
"ناكل ; كفتاجي ; و ; نجم ; نشري ; شوية ; حوت ; زادة\n",
" = ; = ; S ; D ; = ; = ; = ; = \n",
"ناكل ; كفتاجي ; وننجم ; <eps> ; نشري ; شوية ; حوت ; زادة\n",
"================================================================================\n",
"Salah1, %WER 28.57 [ 2 / 7, 0 ins, 1 del, 1 sub ]\n",
"نحب ; ماكلة ; بنينة ; كسكروت ; نظيف ; و ; رخيص\n",
" = ; = ; = ; = ; = ; S ; D \n",
"نحب ; ماكلة ; بنينة ; كسكروت ; نظيف ; ورخيص ; <eps>\n"
]
}
],
"source": [
"filein = \"wer_test_salah.txt\"\n",
"with open(filein, \"r\") as wer : \n",
" lines = wer.read().splitlines()\n",
" print(\"\\n\".join(lines))"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.5"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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