File size: 59,739 Bytes
becc14c
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
{
  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "## Predspracovanie dát\n",
        "\n",
        "Pomocné funkcie využité pre vytvorenie trénovacieho/evaluačného datasetu v tomto notebooku, predspracovávali dáta kombináciou delenia audia na menšie časti na základe detekovania ticha v nahrávkach, resampling dát na 16kHz formát požadovaný modelom, automatickú trasnkripciu ladeným modelom s prvotných tréningov, a navrhnutie rozdelenia nahrávok podľa počtu tokenov na ukončené vety.\n",
        "\n",
        "### Výstupný formát\n",
        "- TSV súbor obsahujúci:\n",
        "    - cestu k zvukovému záznamu\n",
        "    - dĺžku záznamu v sekundách\n",
        "    - transkripciu záznamu\n",
        "\n",
        "\n",
        "### Využité knižnice\n",
        "  - os\n",
        "  - torch\n",
        "  - torchaudio  - Na načitanie a resampling zvukových záznamov\n",
        "  - pydub (AudioSegment, silence)\t- Na spracovanie audia, detekciu ticha, exportovanie častí\n",
        "  - transformers -\tNa načítanie procesora, modelu, a tokenizáciu pre transkripciu\n",
        "  - re - Regulárne výrazy na rozdelenie textu podľa viet.\n",
        "  - pandas - export dát do TSV\n",
        "  - tqdm - monitorovanie priebehu pri spracovaní tokenov\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "id": "dB-uebOX2p8j"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Popis funckii\n",
        "\n",
        "### load_whisper_custom_model\n",
        "- **Parametre :** cesta k modelu\n",
        "- načitanie vlastného modelu pomocou transformers\n",
        "- použitie WhisperProcessor a WhisperForConditionalGeneration\n",
        "- prenesenie modelu na GPU\n",
        "\n",
        "### transcribe_function\n",
        "- **Parametre :** cesta k súboru so zvukovým záznamom, processor, model\n",
        "- Načítanie audia pomocou torchaudio.load.\n",
        "- Ak sampling rate audia ≠ 16000 Hz (cieľ), resampluje sa pomocou torchaudio.transforms.Resample.\n",
        "- Audio sa premení na vstupné features cez processor.feature_extractor.\n",
        "- Forced decoding nastavuje jazyk (\"sk\" = slovenčina) a úlohu (\"transcribe\") cez get_decoder_prompt_ids.\n",
        "- Model generuje text cez beam search (num_beams=5, skoré ukončenie).\n",
        "- Výsledok sa dekóduje cez tokenizer a vráti čistý text.\n",
        "\n",
        "### split_text_by_sentence\n",
        "- **Parametre :** text, maximálny počet tokenov, tokenizer\n",
        "- používa regulárne výrazy na delenie textu po vetách (bodka, otáznik, výkričník)\n",
        "- ak vetu už nemožno pridať do chunku bez prekročenia limitu tokenov (max_tokens), začne nový chunk\n",
        "- okenizácia sa robí pomocou processor.tokenizer(sentence).input_ids\n",
        "\n",
        "\n",
        "### split_and_transcribe_with_token_limit\n",
        "- **Parametre :** cesta k súboru so zvukovým záznamom, processor, model\n",
        "- načítanie audia cez pydub (AudioSegment.from_mp3).\n",
        "- detekcia ticha:\n",
        "  -  pomocou silence.detect_silence(audio, min_silence_len=MIN_SILENCE_LEN, silence_thresh=SILENCE_THRESH)\n",
        "  - detekované tiché body (v strede medzi začiatkom a koncom ticha) sa berú ako potenciálne body delenia\n",
        "- fallback rozdelenie pre dlhé časti (> MAX_CHUNK_MS):\n",
        "- ak chunk je príliš dlhý, skúsi sa ešte jemnejšie delenie s mäkšími kritériami (ALT_MIN_SILENCE_LEN).\n",
        "- export chunkov do .wav formátu.\n",
        "- transkripcia chunkov\n",
        "- v prípade, že text presahuje token limit, text sa rozdelí na viac častí (iba textové rozdelenie).\n",
        "\n",
        "\n",
        "### process_all_mp3\n",
        "- spracovanie všetkých súborov vo formáte mp3 v definovanom priečinku\n",
        "- volá funkcie na spracovanie dát\n",
        "- výstup TSV súbor vo formáte : **path**, **duration**, **sentence**"
      ],
      "metadata": {
        "id": "MV7Dh_Qw-nWV"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Import knižníc"
      ],
      "metadata": {
        "id": "Ybedar-N-957"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "kDNwj9t1qm8w",
        "outputId": "12aca0b1-41c4-4eeb-9dc7-f13a057bde20",
        "collapsed": true
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting pydub\n",
            "  Downloading pydub-0.25.1-py2.py3-none-any.whl.metadata (1.4 kB)\n",
            "Downloading pydub-0.25.1-py2.py3-none-any.whl (32 kB)\n",
            "Installing collected packages: pydub\n",
            "Successfully installed pydub-0.25.1\n"
          ]
        }
      ],
      "source": [
        "!pip install pydub"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "D2MGL2U4q8Iu"
      },
      "outputs": [],
      "source": [
        "import os\n",
        "import pandas as pd\n",
        "import nltk\n",
        "from pydub import AudioSegment, silence\n",
        "from nltk.tokenize import sent_tokenize\n",
        "import re\n",
        "import gc\n",
        "import torch\n",
        "import torchaudio\n",
        "import pandas as pd\n",
        "import soundfile as sf\n",
        "from tqdm import tqdm\n",
        "from pydub import AudioSegment, silence\n",
        "from transformers import WhisperProcessor, WhisperForConditionalGeneration"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Import vlastného modelu implemenácia funkcií\n"
      ],
      "metadata": {
        "id": "ynqsRY58V1ts"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from google.colab import drive\n",
        "\n",
        "drive.mount('/content/drive')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "wiQ3EoJwV6c9",
        "outputId": "6218351e-5d3b-47c8-a6dc-e0bec12abf1a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# === CONFIG ===\n",
        "\n",
        "AUDIO_FOLDER = \"/content/drive/MyDrive/DP_data/audio_files\"\n",
        "OUTPUT_FOLDER = \"/content/drive/MyDrive/DP_data/audio_chunks\"\n",
        "TSV_OUTPUT = \"/content/drive/MyDrive/DP_data/adpocia3.tsv\"\n",
        "MODEL_DIR = \"/content/drive/MyDrive/DP_data/whisper_medium_3d\"\n",
        "\n",
        "TARGET_SAMPLE_RATE = 16000\n",
        "TOKEN_LIMIT = 100\n",
        "MIN_SILENCE_LEN = 400  # Minimum silence length v ms\n",
        "SILENCE_THRESH = -40    # Silence threshold v dB\n",
        "\n",
        "MAX_CHUNK_MS = 28000\n",
        "ALT_MIN_SILENCE_LEN = 200  # mäkšie kritérium pre fallback\n",
        "\n",
        "os.makedirs(OUTPUT_FOLDER, exist_ok=True)\n",
        "\n",
        "# ==== NACITANIE MODELU ====\n",
        "def load_whisper_custom_model(model_dir):\n",
        "    processor = WhisperProcessor.from_pretrained(model_dir)\n",
        "    model = WhisperForConditionalGeneration.from_pretrained(model_dir)\n",
        "    model.eval()\n",
        "    model.to(\"cuda\" if torch.cuda.is_available() else \"cpu\")\n",
        "    return processor, model\n",
        "\n",
        "# ==== TRANSKRIPCIA ====\n",
        "def transcribe_function(path_file, processor, model):\n",
        "    speech_array, sampling_rate = torchaudio.load(path_file)\n",
        "    if sampling_rate != TARGET_SAMPLE_RATE:\n",
        "        resampler = torchaudio.transforms.Resample(orig_freq=sampling_rate, new_freq=TARGET_SAMPLE_RATE)\n",
        "        speech_array = resampler(speech_array)\n",
        "\n",
        "    inputs = processor.feature_extractor(\n",
        "        speech_array.squeeze().numpy(),\n",
        "        sampling_rate=TARGET_SAMPLE_RATE,\n",
        "        return_tensors=\"pt\"\n",
        "    )\n",
        "\n",
        "    forced_decoder_ids = processor.get_decoder_prompt_ids(language=\"sk\", task=\"transcribe\")\n",
        "    input_features = inputs[\"input_features\"].to(model.device)\n",
        "\n",
        "    with torch.no_grad():\n",
        "        generated_ids = model.generate(\n",
        "            input_features,\n",
        "            forced_decoder_ids=forced_decoder_ids,\n",
        "            num_beams=5,\n",
        "            early_stopping=True\n",
        "        )\n",
        "\n",
        "    transcription = processor.tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]\n",
        "    return transcription.strip()\n",
        "\n",
        "# ==== DELENIE TEXTU PODLA VIET ====\n",
        "def split_text_by_sentence(text, max_tokens, tokenizer):\n",
        "    sentences = re.split(r'(?<=[.!?])\\s+', text.strip())\n",
        "    chunks, current_chunk, current_tokens = [], [], 0\n",
        "\n",
        "    for sentence in sentences:\n",
        "        tokens = tokenizer(sentence).input_ids\n",
        "        if current_tokens + len(tokens) > max_tokens and current_chunk:\n",
        "            chunks.append(\" \".join(current_chunk))\n",
        "            current_chunk = [sentence]\n",
        "            current_tokens = len(tokens)\n",
        "        else:\n",
        "            current_chunk.append(sentence)\n",
        "            current_tokens += len(tokens)\n",
        "\n",
        "    if current_chunk:\n",
        "        chunks.append(\" \".join(current_chunk))\n",
        "\n",
        "    return chunks\n",
        "\n",
        "def split_and_transcribe_with_token_limit(mp3_path, processor, model):\n",
        "    audio = AudioSegment.from_mp3(mp3_path)\n",
        "    filename = os.path.splitext(os.path.basename(mp3_path))[0]\n",
        "\n",
        "    silence_points = silence.detect_silence(audio, min_silence_len=MIN_SILENCE_LEN, silence_thresh=SILENCE_THRESH)\n",
        "    silence_points = [((start + end) // 2) for start, end in silence_points]\n",
        "\n",
        "    chunk_starts = [0]\n",
        "    for point in silence_points:\n",
        "        if point - chunk_starts[-1] >= 20000:\n",
        "            chunk_starts.append(point)\n",
        "    chunk_starts.append(len(audio))\n",
        "\n",
        "    adjusted_starts = [chunk_starts[0]]\n",
        "    for i in range(1, len(chunk_starts)):\n",
        "        prev = adjusted_starts[-1]\n",
        "        curr = chunk_starts[i]\n",
        "        duration = curr - prev\n",
        "\n",
        "        if duration > MAX_CHUNK_MS:\n",
        "            long_chunk = audio[prev:curr]\n",
        "            extra_silences = silence.detect_silence(\n",
        "                long_chunk, min_silence_len=ALT_MIN_SILENCE_LEN, silence_thresh=SILENCE_THRESH\n",
        "            )\n",
        "            extra_points = [((start + end) // 2 + prev) for start, end in extra_silences if (start + end)//2 + prev < curr]\n",
        "\n",
        "            if extra_points:\n",
        "                for p in extra_points:\n",
        "                    if p - adjusted_starts[-1] >= 8000:\n",
        "                        adjusted_starts.append(p)\n",
        "                if adjusted_starts[-1] != curr:\n",
        "                    adjusted_starts.append(curr)\n",
        "            else:\n",
        "                adjusted_starts.append(curr)\n",
        "        else:\n",
        "            adjusted_starts.append(curr)\n",
        "\n",
        "    # Transkripcia a tokenové delenie\n",
        "    rows = []\n",
        "    chunk_index = 0\n",
        "\n",
        "    for i in range(len(adjusted_starts) - 1):\n",
        "        start, end = adjusted_starts[i], adjusted_starts[i + 1]\n",
        "        chunk = audio[start:end]\n",
        "        chunk_path = os.path.join(OUTPUT_FOLDER, f\"{filename}_chunk_{chunk_index}.wav\")\n",
        "        chunk.export(chunk_path, format=\"wav\")\n",
        "\n",
        "        transcription = transcribe_function(chunk_path, processor, model)\n",
        "        token_count = len(processor.tokenizer(transcription).input_ids)\n",
        "\n",
        "        if token_count > TOKEN_LIMIT:\n",
        "            sub_chunks = split_text_by_sentence(transcription, TOKEN_LIMIT, processor.tokenizer)\n",
        "\n",
        "            for j, sub_text in enumerate(sub_chunks):\n",
        "                # Vytvorenie navrhu rozdelenia povodneho chunk\n",
        "                new_path = f\"{filename}_chunk_{chunk_index}_p{j+1}.wav\"\n",
        "                rows.append([new_path, round((end - start)/1000, 3), sub_text])\n",
        "        else:\n",
        "            duration_sec = round((end - start) / 1000, 3)\n",
        "            rows.append([os.path.basename(chunk_path), duration_sec, transcription])\n",
        "\n",
        "        chunk_index += 1\n",
        "\n",
        "    return rows\n",
        "\n",
        "def process_all_mp3():\n",
        "\n",
        "    all_rows = []\n",
        "    for file in tqdm(sorted(os.listdir(AUDIO_FOLDER))):\n",
        "        if file.endswith(\".mp3\"):\n",
        "            full_path = os.path.join(AUDIO_FOLDER, file)\n",
        "            rows = split_and_transcribe_with_token_limit(full_path, processor, model)\n",
        "            all_rows.extend(rows)\n",
        "\n",
        "    df = pd.DataFrame(all_rows, columns=[\"path\", \"duration\", \"sentence\"])\n",
        "    df.to_csv(TSV_OUTPUT, sep=\"\\t\", index=False)\n",
        "    print(f\" TSV saved to: {TSV_OUTPUT}\")\n"
      ],
      "metadata": {
        "id": "9ZCdSEiplhyd"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "processor, model = load_whisper_custom_model(MODEL_DIR)"
      ],
      "metadata": {
        "id": "cSCPsy8RljSq"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "pip install git+https://github.com/m-bain/whisperx.git"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "collapsed": true,
        "id": "xNvUOIGyyfF_",
        "outputId": "5f89b7d6-e356-44b5-8d43-f1fcc63bb13c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting git+https://github.com/m-bain/whisperx.git\n",
            "  Cloning https://github.com/m-bain/whisperx.git to /tmp/pip-req-build-y6876pd_\n",
            "  Running command git clone --filter=blob:none --quiet https://github.com/m-bain/whisperx.git /tmp/pip-req-build-y6876pd_\n",
            "  Resolved https://github.com/m-bain/whisperx.git to commit 0aed8745890f12ecfe0b2d9c4ba62bcdfb16f94e\n",
            "  Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n",
            "  Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n",
            "  Preparing metadata (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
            "Collecting ctranslate2>=4.5.0 (from whisperx==3.3.1)\n",
            "  Downloading ctranslate2-4.6.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (10 kB)\n",
            "Collecting faster-whisper>=1.1.1 (from whisperx==3.3.1)\n",
            "  Downloading faster_whisper-1.1.1-py3-none-any.whl.metadata (16 kB)\n",
            "Requirement already satisfied: nltk>=3.9.1 in /usr/local/lib/python3.11/dist-packages (from whisperx==3.3.1) (3.9.1)\n",
            "Requirement already satisfied: numpy>=2.0.2 in /usr/local/lib/python3.11/dist-packages (from whisperx==3.3.1) (2.0.2)\n",
            "Collecting onnxruntime==1.19 (from whisperx==3.3.1)\n",
            "  Downloading onnxruntime-1.19.0-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl.metadata (4.3 kB)\n",
            "Collecting pandas>=2.2.3 (from whisperx==3.3.1)\n",
            "  Downloading pandas-2.2.3-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (89 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m89.9/89.9 kB\u001b[0m \u001b[31m8.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting pyannote-audio>=3.3.2 (from whisperx==3.3.1)\n",
            "  Downloading pyannote.audio-3.3.2-py2.py3-none-any.whl.metadata (11 kB)\n",
            "Requirement already satisfied: torch>=2.5.1 in /usr/local/lib/python3.11/dist-packages (from whisperx==3.3.1) (2.6.0+cu124)\n",
            "Requirement already satisfied: torchaudio>=2.5.1 in /usr/local/lib/python3.11/dist-packages (from whisperx==3.3.1) (2.6.0+cu124)\n",
            "Requirement already satisfied: transformers>=4.48.0 in /usr/local/lib/python3.11/dist-packages (from whisperx==3.3.1) (4.51.3)\n",
            "Collecting coloredlogs (from onnxruntime==1.19->whisperx==3.3.1)\n",
            "  Downloading coloredlogs-15.0.1-py2.py3-none-any.whl.metadata (12 kB)\n",
            "Requirement already satisfied: flatbuffers in /usr/local/lib/python3.11/dist-packages (from onnxruntime==1.19->whisperx==3.3.1) (25.2.10)\n",
            "Requirement already satisfied: packaging in /usr/local/lib/python3.11/dist-packages (from onnxruntime==1.19->whisperx==3.3.1) (24.2)\n",
            "Requirement already satisfied: protobuf in /usr/local/lib/python3.11/dist-packages (from onnxruntime==1.19->whisperx==3.3.1) (5.29.4)\n",
            "Requirement already satisfied: sympy in /usr/local/lib/python3.11/dist-packages (from onnxruntime==1.19->whisperx==3.3.1) (1.13.1)\n",
            "Requirement already satisfied: setuptools in /usr/local/lib/python3.11/dist-packages (from ctranslate2>=4.5.0->whisperx==3.3.1) (75.2.0)\n",
            "Requirement already satisfied: pyyaml<7,>=5.3 in /usr/local/lib/python3.11/dist-packages (from ctranslate2>=4.5.0->whisperx==3.3.1) (6.0.2)\n",
            "Requirement already satisfied: huggingface-hub>=0.13 in /usr/local/lib/python3.11/dist-packages (from faster-whisper>=1.1.1->whisperx==3.3.1) (0.30.2)\n",
            "Requirement already satisfied: tokenizers<1,>=0.13 in /usr/local/lib/python3.11/dist-packages (from faster-whisper>=1.1.1->whisperx==3.3.1) (0.21.1)\n",
            "Collecting av>=11 (from faster-whisper>=1.1.1->whisperx==3.3.1)\n",
            "  Downloading av-14.3.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (4.7 kB)\n",
            "Requirement already satisfied: tqdm in /usr/local/lib/python3.11/dist-packages (from faster-whisper>=1.1.1->whisperx==3.3.1) (4.67.1)\n",
            "Requirement already satisfied: click in /usr/local/lib/python3.11/dist-packages (from nltk>=3.9.1->whisperx==3.3.1) (8.1.8)\n",
            "Requirement already satisfied: joblib in /usr/local/lib/python3.11/dist-packages (from nltk>=3.9.1->whisperx==3.3.1) (1.4.2)\n",
            "Requirement already satisfied: regex>=2021.8.3 in /usr/local/lib/python3.11/dist-packages (from nltk>=3.9.1->whisperx==3.3.1) (2024.11.6)\n",
            "Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.11/dist-packages (from pandas>=2.2.3->whisperx==3.3.1) (2.9.0.post0)\n",
            "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.11/dist-packages (from pandas>=2.2.3->whisperx==3.3.1) (2025.2)\n",
            "Requirement already satisfied: tzdata>=2022.7 in /usr/local/lib/python3.11/dist-packages (from pandas>=2.2.3->whisperx==3.3.1) (2025.2)\n",
            "Collecting asteroid-filterbanks>=0.4 (from pyannote-audio>=3.3.2->whisperx==3.3.1)\n",
            "  Downloading asteroid_filterbanks-0.4.0-py3-none-any.whl.metadata (3.3 kB)\n",
            "Requirement already satisfied: einops>=0.6.0 in /usr/local/lib/python3.11/dist-packages (from pyannote-audio>=3.3.2->whisperx==3.3.1) (0.8.1)\n",
            "Collecting lightning>=2.0.1 (from pyannote-audio>=3.3.2->whisperx==3.3.1)\n",
            "  Downloading lightning-2.5.1.post0-py3-none-any.whl.metadata (39 kB)\n",
            "Collecting omegaconf<3.0,>=2.1 (from pyannote-audio>=3.3.2->whisperx==3.3.1)\n",
            "  Downloading omegaconf-2.3.0-py3-none-any.whl.metadata (3.9 kB)\n",
            "Collecting pyannote.core>=5.0.0 (from pyannote-audio>=3.3.2->whisperx==3.3.1)\n",
            "  Downloading pyannote.core-5.0.0-py3-none-any.whl.metadata (1.4 kB)\n",
            "Collecting pyannote.database>=5.0.1 (from pyannote-audio>=3.3.2->whisperx==3.3.1)\n",
            "  Downloading pyannote.database-5.1.3-py3-none-any.whl.metadata (1.1 kB)\n",
            "Collecting pyannote.metrics>=3.2 (from pyannote-audio>=3.3.2->whisperx==3.3.1)\n",
            "  Downloading pyannote.metrics-3.2.1-py3-none-any.whl.metadata (1.3 kB)\n",
            "Collecting pyannote.pipeline>=3.0.1 (from pyannote-audio>=3.3.2->whisperx==3.3.1)\n",
            "  Downloading pyannote.pipeline-3.0.1-py3-none-any.whl.metadata (897 bytes)\n",
            "Collecting pytorch-metric-learning>=2.1.0 (from pyannote-audio>=3.3.2->whisperx==3.3.1)\n",
            "  Downloading pytorch_metric_learning-2.8.1-py3-none-any.whl.metadata (18 kB)\n",
            "Requirement already satisfied: rich>=12.0.0 in /usr/local/lib/python3.11/dist-packages (from pyannote-audio>=3.3.2->whisperx==3.3.1) (13.9.4)\n",
            "Collecting semver>=3.0.0 (from pyannote-audio>=3.3.2->whisperx==3.3.1)\n",
            "  Downloading semver-3.0.4-py3-none-any.whl.metadata (6.8 kB)\n",
            "Requirement already satisfied: soundfile>=0.12.1 in /usr/local/lib/python3.11/dist-packages (from pyannote-audio>=3.3.2->whisperx==3.3.1) (0.13.1)\n",
            "Collecting speechbrain>=1.0.0 (from pyannote-audio>=3.3.2->whisperx==3.3.1)\n",
            "  Downloading speechbrain-1.0.3-py3-none-any.whl.metadata (24 kB)\n",
            "Collecting tensorboardX>=2.6 (from pyannote-audio>=3.3.2->whisperx==3.3.1)\n",
            "  Downloading tensorboardX-2.6.2.2-py2.py3-none-any.whl.metadata (5.8 kB)\n",
            "Collecting torch-audiomentations>=0.11.0 (from pyannote-audio>=3.3.2->whisperx==3.3.1)\n",
            "  Downloading torch_audiomentations-0.12.0-py3-none-any.whl.metadata (15 kB)\n",
            "Collecting torchmetrics>=0.11.0 (from pyannote-audio>=3.3.2->whisperx==3.3.1)\n",
            "  Downloading torchmetrics-1.7.1-py3-none-any.whl.metadata (21 kB)\n",
            "Requirement already satisfied: filelock in /usr/local/lib/python3.11/dist-packages (from torch>=2.5.1->whisperx==3.3.1) (3.18.0)\n",
            "Requirement already satisfied: typing-extensions>=4.10.0 in /usr/local/lib/python3.11/dist-packages (from torch>=2.5.1->whisperx==3.3.1) (4.13.2)\n",
            "Requirement already satisfied: networkx in /usr/local/lib/python3.11/dist-packages (from torch>=2.5.1->whisperx==3.3.1) (3.4.2)\n",
            "Requirement already satisfied: jinja2 in /usr/local/lib/python3.11/dist-packages (from torch>=2.5.1->whisperx==3.3.1) (3.1.6)\n",
            "Requirement already satisfied: fsspec in /usr/local/lib/python3.11/dist-packages (from torch>=2.5.1->whisperx==3.3.1) (2025.3.2)\n",
            "Collecting nvidia-cuda-nvrtc-cu12==12.4.127 (from torch>=2.5.1->whisperx==3.3.1)\n",
            "  Downloading nvidia_cuda_nvrtc_cu12-12.4.127-py3-none-manylinux2014_x86_64.whl.metadata (1.5 kB)\n",
            "Collecting nvidia-cuda-runtime-cu12==12.4.127 (from torch>=2.5.1->whisperx==3.3.1)\n",
            "  Downloading nvidia_cuda_runtime_cu12-12.4.127-py3-none-manylinux2014_x86_64.whl.metadata (1.5 kB)\n",
            "Collecting nvidia-cuda-cupti-cu12==12.4.127 (from torch>=2.5.1->whisperx==3.3.1)\n",
            "  Downloading nvidia_cuda_cupti_cu12-12.4.127-py3-none-manylinux2014_x86_64.whl.metadata (1.6 kB)\n",
            "Collecting nvidia-cudnn-cu12==9.1.0.70 (from torch>=2.5.1->whisperx==3.3.1)\n",
            "  Downloading nvidia_cudnn_cu12-9.1.0.70-py3-none-manylinux2014_x86_64.whl.metadata (1.6 kB)\n",
            "Collecting nvidia-cublas-cu12==12.4.5.8 (from torch>=2.5.1->whisperx==3.3.1)\n",
            "  Downloading nvidia_cublas_cu12-12.4.5.8-py3-none-manylinux2014_x86_64.whl.metadata (1.5 kB)\n",
            "Collecting nvidia-cufft-cu12==11.2.1.3 (from torch>=2.5.1->whisperx==3.3.1)\n",
            "  Downloading nvidia_cufft_cu12-11.2.1.3-py3-none-manylinux2014_x86_64.whl.metadata (1.5 kB)\n",
            "Collecting nvidia-curand-cu12==10.3.5.147 (from torch>=2.5.1->whisperx==3.3.1)\n",
            "  Downloading nvidia_curand_cu12-10.3.5.147-py3-none-manylinux2014_x86_64.whl.metadata (1.5 kB)\n",
            "Collecting nvidia-cusolver-cu12==11.6.1.9 (from torch>=2.5.1->whisperx==3.3.1)\n",
            "  Downloading nvidia_cusolver_cu12-11.6.1.9-py3-none-manylinux2014_x86_64.whl.metadata (1.6 kB)\n",
            "Collecting nvidia-cusparse-cu12==12.3.1.170 (from torch>=2.5.1->whisperx==3.3.1)\n",
            "  Downloading nvidia_cusparse_cu12-12.3.1.170-py3-none-manylinux2014_x86_64.whl.metadata (1.6 kB)\n",
            "Requirement already satisfied: nvidia-cusparselt-cu12==0.6.2 in /usr/local/lib/python3.11/dist-packages (from torch>=2.5.1->whisperx==3.3.1) (0.6.2)\n",
            "Requirement already satisfied: nvidia-nccl-cu12==2.21.5 in /usr/local/lib/python3.11/dist-packages (from torch>=2.5.1->whisperx==3.3.1) (2.21.5)\n",
            "Requirement already satisfied: nvidia-nvtx-cu12==12.4.127 in /usr/local/lib/python3.11/dist-packages (from torch>=2.5.1->whisperx==3.3.1) (12.4.127)\n",
            "Collecting nvidia-nvjitlink-cu12==12.4.127 (from torch>=2.5.1->whisperx==3.3.1)\n",
            "  Downloading nvidia_nvjitlink_cu12-12.4.127-py3-none-manylinux2014_x86_64.whl.metadata (1.5 kB)\n",
            "Requirement already satisfied: triton==3.2.0 in /usr/local/lib/python3.11/dist-packages (from torch>=2.5.1->whisperx==3.3.1) (3.2.0)\n",
            "Requirement already satisfied: mpmath<1.4,>=1.1.0 in /usr/local/lib/python3.11/dist-packages (from sympy->onnxruntime==1.19->whisperx==3.3.1) (1.3.0)\n",
            "Requirement already satisfied: requests in /usr/local/lib/python3.11/dist-packages (from transformers>=4.48.0->whisperx==3.3.1) (2.32.3)\n",
            "Requirement already satisfied: safetensors>=0.4.3 in /usr/local/lib/python3.11/dist-packages (from transformers>=4.48.0->whisperx==3.3.1) (0.5.3)\n",
            "Collecting lightning-utilities<2.0,>=0.10.0 (from lightning>=2.0.1->pyannote-audio>=3.3.2->whisperx==3.3.1)\n",
            "  Downloading lightning_utilities-0.14.3-py3-none-any.whl.metadata (5.6 kB)\n",
            "Collecting pytorch-lightning (from lightning>=2.0.1->pyannote-audio>=3.3.2->whisperx==3.3.1)\n",
            "  Downloading pytorch_lightning-2.5.1.post0-py3-none-any.whl.metadata (20 kB)\n",
            "Collecting antlr4-python3-runtime==4.9.* (from omegaconf<3.0,>=2.1->pyannote-audio>=3.3.2->whisperx==3.3.1)\n",
            "  Downloading antlr4-python3-runtime-4.9.3.tar.gz (117 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m117.0/117.0 kB\u001b[0m \u001b[31m13.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "Requirement already satisfied: sortedcontainers>=2.0.4 in /usr/local/lib/python3.11/dist-packages (from pyannote.core>=5.0.0->pyannote-audio>=3.3.2->whisperx==3.3.1) (2.4.0)\n",
            "Requirement already satisfied: scipy>=1.1 in /usr/local/lib/python3.11/dist-packages (from pyannote.core>=5.0.0->pyannote-audio>=3.3.2->whisperx==3.3.1) (1.15.2)\n",
            "Requirement already satisfied: typer>=0.12.1 in /usr/local/lib/python3.11/dist-packages (from pyannote.database>=5.0.1->pyannote-audio>=3.3.2->whisperx==3.3.1) (0.15.2)\n",
            "Requirement already satisfied: scikit-learn>=0.17.1 in /usr/local/lib/python3.11/dist-packages (from pyannote.metrics>=3.2->pyannote-audio>=3.3.2->whisperx==3.3.1) (1.6.1)\n",
            "Collecting docopt>=0.6.2 (from pyannote.metrics>=3.2->pyannote-audio>=3.3.2->whisperx==3.3.1)\n",
            "  Downloading docopt-0.6.2.tar.gz (25 kB)\n",
            "  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "Requirement already satisfied: tabulate>=0.7.7 in /usr/local/lib/python3.11/dist-packages (from pyannote.metrics>=3.2->pyannote-audio>=3.3.2->whisperx==3.3.1) (0.9.0)\n",
            "Requirement already satisfied: matplotlib>=2.0.0 in /usr/local/lib/python3.11/dist-packages (from pyannote.metrics>=3.2->pyannote-audio>=3.3.2->whisperx==3.3.1) (3.10.0)\n",
            "Collecting optuna>=3.1 (from pyannote.pipeline>=3.0.1->pyannote-audio>=3.3.2->whisperx==3.3.1)\n",
            "  Downloading optuna-4.3.0-py3-none-any.whl.metadata (17 kB)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.11/dist-packages (from python-dateutil>=2.8.2->pandas>=2.2.3->whisperx==3.3.1) (1.17.0)\n",
            "Requirement already satisfied: markdown-it-py>=2.2.0 in /usr/local/lib/python3.11/dist-packages (from rich>=12.0.0->pyannote-audio>=3.3.2->whisperx==3.3.1) (3.0.0)\n",
            "Requirement already satisfied: pygments<3.0.0,>=2.13.0 in /usr/local/lib/python3.11/dist-packages (from rich>=12.0.0->pyannote-audio>=3.3.2->whisperx==3.3.1) (2.19.1)\n",
            "Requirement already satisfied: cffi>=1.0 in /usr/local/lib/python3.11/dist-packages (from soundfile>=0.12.1->pyannote-audio>=3.3.2->whisperx==3.3.1) (1.17.1)\n",
            "Collecting hyperpyyaml (from speechbrain>=1.0.0->pyannote-audio>=3.3.2->whisperx==3.3.1)\n",
            "  Downloading HyperPyYAML-1.2.2-py3-none-any.whl.metadata (7.6 kB)\n",
            "Requirement already satisfied: sentencepiece in /usr/local/lib/python3.11/dist-packages (from speechbrain>=1.0.0->pyannote-audio>=3.3.2->whisperx==3.3.1) (0.2.0)\n",
            "Collecting julius<0.3,>=0.2.3 (from torch-audiomentations>=0.11.0->pyannote-audio>=3.3.2->whisperx==3.3.1)\n",
            "  Downloading julius-0.2.7.tar.gz (59 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m59.6/59.6 kB\u001b[0m \u001b[31m6.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "Collecting torch-pitch-shift>=1.2.2 (from torch-audiomentations>=0.11.0->pyannote-audio>=3.3.2->whisperx==3.3.1)\n",
            "  Downloading torch_pitch_shift-1.2.5-py3-none-any.whl.metadata (2.5 kB)\n",
            "Collecting humanfriendly>=9.1 (from coloredlogs->onnxruntime==1.19->whisperx==3.3.1)\n",
            "  Downloading humanfriendly-10.0-py2.py3-none-any.whl.metadata (9.2 kB)\n",
            "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.11/dist-packages (from jinja2->torch>=2.5.1->whisperx==3.3.1) (3.0.2)\n",
            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.11/dist-packages (from requests->transformers>=4.48.0->whisperx==3.3.1) (3.4.1)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.11/dist-packages (from requests->transformers>=4.48.0->whisperx==3.3.1) (3.10)\n",
            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.11/dist-packages (from requests->transformers>=4.48.0->whisperx==3.3.1) (2.4.0)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.11/dist-packages (from requests->transformers>=4.48.0->whisperx==3.3.1) (2025.1.31)\n",
            "Requirement already satisfied: pycparser in /usr/local/lib/python3.11/dist-packages (from cffi>=1.0->soundfile>=0.12.1->pyannote-audio>=3.3.2->whisperx==3.3.1) (2.22)\n",
            "Requirement already satisfied: aiohttp!=4.0.0a0,!=4.0.0a1 in /usr/local/lib/python3.11/dist-packages (from fsspec[http]<2026.0,>=2022.5.0->lightning>=2.0.1->pyannote-audio>=3.3.2->whisperx==3.3.1) (3.11.15)\n",
            "Requirement already satisfied: mdurl~=0.1 in /usr/local/lib/python3.11/dist-packages (from markdown-it-py>=2.2.0->rich>=12.0.0->pyannote-audio>=3.3.2->whisperx==3.3.1) (0.1.2)\n",
            "Requirement already satisfied: contourpy>=1.0.1 in /usr/local/lib/python3.11/dist-packages (from matplotlib>=2.0.0->pyannote.metrics>=3.2->pyannote-audio>=3.3.2->whisperx==3.3.1) (1.3.2)\n",
            "Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.11/dist-packages (from matplotlib>=2.0.0->pyannote.metrics>=3.2->pyannote-audio>=3.3.2->whisperx==3.3.1) (0.12.1)\n",
            "Requirement already satisfied: fonttools>=4.22.0 in /usr/local/lib/python3.11/dist-packages (from matplotlib>=2.0.0->pyannote.metrics>=3.2->pyannote-audio>=3.3.2->whisperx==3.3.1) (4.57.0)\n",
            "Requirement already satisfied: kiwisolver>=1.3.1 in /usr/local/lib/python3.11/dist-packages (from matplotlib>=2.0.0->pyannote.metrics>=3.2->pyannote-audio>=3.3.2->whisperx==3.3.1) (1.4.8)\n",
            "Requirement already satisfied: pillow>=8 in /usr/local/lib/python3.11/dist-packages (from matplotlib>=2.0.0->pyannote.metrics>=3.2->pyannote-audio>=3.3.2->whisperx==3.3.1) (11.2.1)\n",
            "Requirement already satisfied: pyparsing>=2.3.1 in /usr/local/lib/python3.11/dist-packages (from matplotlib>=2.0.0->pyannote.metrics>=3.2->pyannote-audio>=3.3.2->whisperx==3.3.1) (3.2.3)\n",
            "Collecting alembic>=1.5.0 (from optuna>=3.1->pyannote.pipeline>=3.0.1->pyannote-audio>=3.3.2->whisperx==3.3.1)\n",
            "  Downloading alembic-1.15.2-py3-none-any.whl.metadata (7.3 kB)\n",
            "Collecting colorlog (from optuna>=3.1->pyannote.pipeline>=3.0.1->pyannote-audio>=3.3.2->whisperx==3.3.1)\n",
            "  Downloading colorlog-6.9.0-py3-none-any.whl.metadata (10 kB)\n",
            "Requirement already satisfied: sqlalchemy>=1.4.2 in /usr/local/lib/python3.11/dist-packages (from optuna>=3.1->pyannote.pipeline>=3.0.1->pyannote-audio>=3.3.2->whisperx==3.3.1) (2.0.40)\n",
            "Requirement already satisfied: threadpoolctl>=3.1.0 in /usr/local/lib/python3.11/dist-packages (from scikit-learn>=0.17.1->pyannote.metrics>=3.2->pyannote-audio>=3.3.2->whisperx==3.3.1) (3.6.0)\n",
            "Collecting primePy>=1.3 (from torch-pitch-shift>=1.2.2->torch-audiomentations>=0.11.0->pyannote-audio>=3.3.2->whisperx==3.3.1)\n",
            "  Downloading primePy-1.3-py3-none-any.whl.metadata (4.8 kB)\n",
            "Requirement already satisfied: shellingham>=1.3.0 in /usr/local/lib/python3.11/dist-packages (from typer>=0.12.1->pyannote.database>=5.0.1->pyannote-audio>=3.3.2->whisperx==3.3.1) (1.5.4)\n",
            "Collecting ruamel.yaml>=0.17.28 (from hyperpyyaml->speechbrain>=1.0.0->pyannote-audio>=3.3.2->whisperx==3.3.1)\n",
            "  Downloading ruamel.yaml-0.18.10-py3-none-any.whl.metadata (23 kB)\n",
            "Requirement already satisfied: aiohappyeyeballs>=2.3.0 in /usr/local/lib/python3.11/dist-packages (from aiohttp!=4.0.0a0,!=4.0.0a1->fsspec[http]<2026.0,>=2022.5.0->lightning>=2.0.1->pyannote-audio>=3.3.2->whisperx==3.3.1) (2.6.1)\n",
            "Requirement already satisfied: aiosignal>=1.1.2 in /usr/local/lib/python3.11/dist-packages (from aiohttp!=4.0.0a0,!=4.0.0a1->fsspec[http]<2026.0,>=2022.5.0->lightning>=2.0.1->pyannote-audio>=3.3.2->whisperx==3.3.1) (1.3.2)\n",
            "Requirement already satisfied: attrs>=17.3.0 in /usr/local/lib/python3.11/dist-packages (from aiohttp!=4.0.0a0,!=4.0.0a1->fsspec[http]<2026.0,>=2022.5.0->lightning>=2.0.1->pyannote-audio>=3.3.2->whisperx==3.3.1) (25.3.0)\n",
            "Requirement already satisfied: frozenlist>=1.1.1 in /usr/local/lib/python3.11/dist-packages (from aiohttp!=4.0.0a0,!=4.0.0a1->fsspec[http]<2026.0,>=2022.5.0->lightning>=2.0.1->pyannote-audio>=3.3.2->whisperx==3.3.1) (1.6.0)\n",
            "Requirement already satisfied: multidict<7.0,>=4.5 in /usr/local/lib/python3.11/dist-packages (from aiohttp!=4.0.0a0,!=4.0.0a1->fsspec[http]<2026.0,>=2022.5.0->lightning>=2.0.1->pyannote-audio>=3.3.2->whisperx==3.3.1) (6.4.3)\n",
            "Requirement already satisfied: propcache>=0.2.0 in /usr/local/lib/python3.11/dist-packages (from aiohttp!=4.0.0a0,!=4.0.0a1->fsspec[http]<2026.0,>=2022.5.0->lightning>=2.0.1->pyannote-audio>=3.3.2->whisperx==3.3.1) (0.3.1)\n",
            "Requirement already satisfied: yarl<2.0,>=1.17.0 in /usr/local/lib/python3.11/dist-packages (from aiohttp!=4.0.0a0,!=4.0.0a1->fsspec[http]<2026.0,>=2022.5.0->lightning>=2.0.1->pyannote-audio>=3.3.2->whisperx==3.3.1) (1.20.0)\n",
            "Requirement already satisfied: Mako in /usr/lib/python3/dist-packages (from alembic>=1.5.0->optuna>=3.1->pyannote.pipeline>=3.0.1->pyannote-audio>=3.3.2->whisperx==3.3.1) (1.1.3)\n",
            "Collecting ruamel.yaml.clib>=0.2.7 (from ruamel.yaml>=0.17.28->hyperpyyaml->speechbrain>=1.0.0->pyannote-audio>=3.3.2->whisperx==3.3.1)\n",
            "  Downloading ruamel.yaml.clib-0.2.12-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (2.7 kB)\n",
            "Requirement already satisfied: greenlet>=1 in /usr/local/lib/python3.11/dist-packages (from sqlalchemy>=1.4.2->optuna>=3.1->pyannote.pipeline>=3.0.1->pyannote-audio>=3.3.2->whisperx==3.3.1) (3.2.1)\n",
            "Downloading onnxruntime-1.19.0-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl (13.2 MB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m13.2/13.2 MB\u001b[0m \u001b[31m103.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading ctranslate2-4.6.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (38.6 MB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m38.6/38.6 MB\u001b[0m \u001b[31m16.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading faster_whisper-1.1.1-py3-none-any.whl (1.1 MB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.1/1.1 MB\u001b[0m \u001b[31m60.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading pandas-2.2.3-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (13.1 MB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m13.1/13.1 MB\u001b[0m \u001b[31m126.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading pyannote.audio-3.3.2-py2.py3-none-any.whl (898 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m898.7/898.7 kB\u001b[0m \u001b[31m58.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading nvidia_cublas_cu12-12.4.5.8-py3-none-manylinux2014_x86_64.whl (363.4 MB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m363.4/363.4 MB\u001b[0m \u001b[31m4.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading nvidia_cuda_cupti_cu12-12.4.127-py3-none-manylinux2014_x86_64.whl (13.8 MB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m13.8/13.8 MB\u001b[0m \u001b[31m70.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading nvidia_cuda_nvrtc_cu12-12.4.127-py3-none-manylinux2014_x86_64.whl (24.6 MB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m24.6/24.6 MB\u001b[0m \u001b[31m37.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading nvidia_cuda_runtime_cu12-12.4.127-py3-none-manylinux2014_x86_64.whl (883 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m883.7/883.7 kB\u001b[0m \u001b[31m54.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading nvidia_cudnn_cu12-9.1.0.70-py3-none-manylinux2014_x86_64.whl (664.8 MB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m664.8/664.8 MB\u001b[0m \u001b[31m2.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading nvidia_cufft_cu12-11.2.1.3-py3-none-manylinux2014_x86_64.whl (211.5 MB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m211.5/211.5 MB\u001b[0m \u001b[31m6.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading nvidia_curand_cu12-10.3.5.147-py3-none-manylinux2014_x86_64.whl (56.3 MB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m56.3/56.3 MB\u001b[0m \u001b[31m14.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading nvidia_cusolver_cu12-11.6.1.9-py3-none-manylinux2014_x86_64.whl (127.9 MB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m127.9/127.9 MB\u001b[0m \u001b[31m7.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading nvidia_cusparse_cu12-12.3.1.170-py3-none-manylinux2014_x86_64.whl (207.5 MB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m207.5/207.5 MB\u001b[0m \u001b[31m5.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading nvidia_nvjitlink_cu12-12.4.127-py3-none-manylinux2014_x86_64.whl (21.1 MB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m21.1/21.1 MB\u001b[0m \u001b[31m76.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading asteroid_filterbanks-0.4.0-py3-none-any.whl (29 kB)\n",
            "Downloading av-14.3.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (35.2 MB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m35.2/35.2 MB\u001b[0m \u001b[31m16.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading lightning-2.5.1.post0-py3-none-any.whl (819 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m819.0/819.0 kB\u001b[0m \u001b[31m49.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading omegaconf-2.3.0-py3-none-any.whl (79 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m79.5/79.5 kB\u001b[0m \u001b[31m7.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading pyannote.core-5.0.0-py3-none-any.whl (58 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m58.5/58.5 kB\u001b[0m \u001b[31m5.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading pyannote.database-5.1.3-py3-none-any.whl (48 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m48.1/48.1 kB\u001b[0m \u001b[31m4.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading pyannote.metrics-3.2.1-py3-none-any.whl (51 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m51.4/51.4 kB\u001b[0m \u001b[31m5.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading pyannote.pipeline-3.0.1-py3-none-any.whl (31 kB)\n",
            "Downloading pytorch_metric_learning-2.8.1-py3-none-any.whl (125 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m125.9/125.9 kB\u001b[0m \u001b[31m12.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading semver-3.0.4-py3-none-any.whl (17 kB)\n",
            "Downloading speechbrain-1.0.3-py3-none-any.whl (864 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m864.1/864.1 kB\u001b[0m \u001b[31m51.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading tensorboardX-2.6.2.2-py2.py3-none-any.whl (101 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m101.7/101.7 kB\u001b[0m \u001b[31m10.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading torch_audiomentations-0.12.0-py3-none-any.whl (48 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m48.5/48.5 kB\u001b[0m \u001b[31m4.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading torchmetrics-1.7.1-py3-none-any.whl (961 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m961.5/961.5 kB\u001b[0m \u001b[31m55.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading coloredlogs-15.0.1-py2.py3-none-any.whl (46 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m46.0/46.0 kB\u001b[0m \u001b[31m4.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading humanfriendly-10.0-py2.py3-none-any.whl (86 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m86.8/86.8 kB\u001b[0m \u001b[31m8.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading lightning_utilities-0.14.3-py3-none-any.whl (28 kB)\n",
            "Downloading optuna-4.3.0-py3-none-any.whl (386 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m386.6/386.6 kB\u001b[0m \u001b[31m33.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading torch_pitch_shift-1.2.5-py3-none-any.whl (5.0 kB)\n",
            "Downloading HyperPyYAML-1.2.2-py3-none-any.whl (16 kB)\n",
            "Downloading pytorch_lightning-2.5.1.post0-py3-none-any.whl (823 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m823.1/823.1 kB\u001b[0m \u001b[31m54.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading alembic-1.15.2-py3-none-any.whl (231 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m231.9/231.9 kB\u001b[0m \u001b[31m23.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading primePy-1.3-py3-none-any.whl (4.0 kB)\n",
            "Downloading ruamel.yaml-0.18.10-py3-none-any.whl (117 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m117.7/117.7 kB\u001b[0m \u001b[31m11.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading colorlog-6.9.0-py3-none-any.whl (11 kB)\n",
            "Downloading ruamel.yaml.clib-0.2.12-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (739 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m739.1/739.1 kB\u001b[0m \u001b[31m52.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hBuilding wheels for collected packages: whisperx, antlr4-python3-runtime, docopt, julius\n",
            "  Building wheel for whisperx (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for whisperx: filename=whisperx-3.3.1-py3-none-any.whl size=16482009 sha256=ce99924c11e21b4f22fc01e88822fc918268d56bd7f675119ccdf611d1f78640\n",
            "  Stored in directory: /tmp/pip-ephem-wheel-cache-l7xwr65x/wheels/a7/c5/cb/f337e8d88ff15af9ece963912a153e4132d00e7cdd61f48416\n",
            "  Building wheel for antlr4-python3-runtime (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for antlr4-python3-runtime: filename=antlr4_python3_runtime-4.9.3-py3-none-any.whl size=144554 sha256=b51000eededb4a85c6a278733c1a114ae6ffe6d4761728c5c5a60d8a5fe3c45e\n",
            "  Stored in directory: /root/.cache/pip/wheels/1a/97/32/461f837398029ad76911109f07047fde1d7b661a147c7c56d1\n",
            "  Building wheel for docopt (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for docopt: filename=docopt-0.6.2-py2.py3-none-any.whl size=13706 sha256=9da05d25e10ee22a692e794b10e0ddb5a5740525a248a2b6bab8281a4a6f3dfe\n",
            "  Stored in directory: /root/.cache/pip/wheels/1a/b0/8c/4b75c4116c31f83c8f9f047231251e13cc74481cca4a78a9ce\n",
            "  Building wheel for julius (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for julius: filename=julius-0.2.7-py3-none-any.whl size=21870 sha256=e53b0a316db08563d285c0acba335e19c47be9589ec9f5ede7aafdb611fd9436\n",
            "  Stored in directory: /root/.cache/pip/wheels/16/15/d4/edd724cefe78050a6ba3344b8b0c6672db829a799dbb9f81ff\n",
            "Successfully built whisperx antlr4-python3-runtime docopt julius\n",
            "Installing collected packages: primePy, docopt, antlr4-python3-runtime, tensorboardX, semver, ruamel.yaml.clib, omegaconf, nvidia-nvjitlink-cu12, nvidia-curand-cu12, nvidia-cufft-cu12, nvidia-cuda-runtime-cu12, nvidia-cuda-nvrtc-cu12, nvidia-cuda-cupti-cu12, nvidia-cublas-cu12, lightning-utilities, humanfriendly, ctranslate2, colorlog, av, ruamel.yaml, pyannote.core, pandas, nvidia-cusparse-cu12, nvidia-cudnn-cu12, coloredlogs, alembic, optuna, onnxruntime, nvidia-cusolver-cu12, hyperpyyaml, pyannote.database, faster-whisper, torchmetrics, pytorch-metric-learning, pyannote.pipeline, pyannote.metrics, julius, asteroid-filterbanks, torch-pitch-shift, speechbrain, pytorch-lightning, torch-audiomentations, lightning, pyannote-audio, whisperx\n",
            "  Attempting uninstall: nvidia-nvjitlink-cu12\n",
            "    Found existing installation: nvidia-nvjitlink-cu12 12.5.82\n",
            "    Uninstalling nvidia-nvjitlink-cu12-12.5.82:\n",
            "      Successfully uninstalled nvidia-nvjitlink-cu12-12.5.82\n",
            "  Attempting uninstall: nvidia-curand-cu12\n",
            "    Found existing installation: nvidia-curand-cu12 10.3.6.82\n",
            "    Uninstalling nvidia-curand-cu12-10.3.6.82:\n",
            "      Successfully uninstalled nvidia-curand-cu12-10.3.6.82\n",
            "  Attempting uninstall: nvidia-cufft-cu12\n",
            "    Found existing installation: nvidia-cufft-cu12 11.2.3.61\n",
            "    Uninstalling nvidia-cufft-cu12-11.2.3.61:\n",
            "      Successfully uninstalled nvidia-cufft-cu12-11.2.3.61\n",
            "  Attempting uninstall: nvidia-cuda-runtime-cu12\n",
            "    Found existing installation: nvidia-cuda-runtime-cu12 12.5.82\n",
            "    Uninstalling nvidia-cuda-runtime-cu12-12.5.82:\n",
            "      Successfully uninstalled nvidia-cuda-runtime-cu12-12.5.82\n",
            "  Attempting uninstall: nvidia-cuda-nvrtc-cu12\n",
            "    Found existing installation: nvidia-cuda-nvrtc-cu12 12.5.82\n",
            "    Uninstalling nvidia-cuda-nvrtc-cu12-12.5.82:\n",
            "      Successfully uninstalled nvidia-cuda-nvrtc-cu12-12.5.82\n",
            "  Attempting uninstall: nvidia-cuda-cupti-cu12\n",
            "    Found existing installation: nvidia-cuda-cupti-cu12 12.5.82\n",
            "    Uninstalling nvidia-cuda-cupti-cu12-12.5.82:\n",
            "      Successfully uninstalled nvidia-cuda-cupti-cu12-12.5.82\n",
            "  Attempting uninstall: nvidia-cublas-cu12\n",
            "    Found existing installation: nvidia-cublas-cu12 12.5.3.2\n",
            "    Uninstalling nvidia-cublas-cu12-12.5.3.2:\n",
            "      Successfully uninstalled nvidia-cublas-cu12-12.5.3.2\n",
            "  Attempting uninstall: pandas\n",
            "    Found existing installation: pandas 2.2.2\n",
            "    Uninstalling pandas-2.2.2:\n",
            "      Successfully uninstalled pandas-2.2.2\n",
            "  Attempting uninstall: nvidia-cusparse-cu12\n",
            "    Found existing installation: nvidia-cusparse-cu12 12.5.1.3\n",
            "    Uninstalling nvidia-cusparse-cu12-12.5.1.3:\n",
            "      Successfully uninstalled nvidia-cusparse-cu12-12.5.1.3\n",
            "  Attempting uninstall: nvidia-cudnn-cu12\n",
            "    Found existing installation: nvidia-cudnn-cu12 9.3.0.75\n",
            "    Uninstalling nvidia-cudnn-cu12-9.3.0.75:\n",
            "      Successfully uninstalled nvidia-cudnn-cu12-9.3.0.75\n",
            "  Attempting uninstall: nvidia-cusolver-cu12\n",
            "    Found existing installation: nvidia-cusolver-cu12 11.6.3.83\n",
            "    Uninstalling nvidia-cusolver-cu12-11.6.3.83:\n",
            "      Successfully uninstalled nvidia-cusolver-cu12-11.6.3.83\n",
            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
            "google-colab 1.0.0 requires pandas==2.2.2, but you have pandas 2.2.3 which is incompatible.\u001b[0m\u001b[31m\n",
            "\u001b[0mSuccessfully installed alembic-1.15.2 antlr4-python3-runtime-4.9.3 asteroid-filterbanks-0.4.0 av-14.3.0 coloredlogs-15.0.1 colorlog-6.9.0 ctranslate2-4.6.0 docopt-0.6.2 faster-whisper-1.1.1 humanfriendly-10.0 hyperpyyaml-1.2.2 julius-0.2.7 lightning-2.5.1.post0 lightning-utilities-0.14.3 nvidia-cublas-cu12-12.4.5.8 nvidia-cuda-cupti-cu12-12.4.127 nvidia-cuda-nvrtc-cu12-12.4.127 nvidia-cuda-runtime-cu12-12.4.127 nvidia-cudnn-cu12-9.1.0.70 nvidia-cufft-cu12-11.2.1.3 nvidia-curand-cu12-10.3.5.147 nvidia-cusolver-cu12-11.6.1.9 nvidia-cusparse-cu12-12.3.1.170 nvidia-nvjitlink-cu12-12.4.127 omegaconf-2.3.0 onnxruntime-1.19.0 optuna-4.3.0 pandas-2.2.3 primePy-1.3 pyannote-audio-3.3.2 pyannote.core-5.0.0 pyannote.database-5.1.3 pyannote.metrics-3.2.1 pyannote.pipeline-3.0.1 pytorch-lightning-2.5.1.post0 pytorch-metric-learning-2.8.1 ruamel.yaml-0.18.10 ruamel.yaml.clib-0.2.12 semver-3.0.4 speechbrain-1.0.3 tensorboardX-2.6.2.2 torch-audiomentations-0.12.0 torch-pitch-shift-1.2.5 torchmetrics-1.7.1 whisperx-3.3.1\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.colab-display-data+json": {
              "pip_warning": {
                "packages": [
                  "nvidia",
                  "pydevd_plugins"
                ]
              },
              "id": "1fe374a7d4d44a3fa775a6ea8224e42e"
            }
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Spracovanie zvukového záznamu"
      ],
      "metadata": {
        "id": "xYfl52w6k6ZW"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "process_all_mp3()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "XW4oyHCYmSuD",
        "outputId": "0a3c717d-dfce-4206-9300-315a10e3fe6b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "100%|██████████| 1/1 [33:09<00:00, 1989.32s/it]"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            " TSV saved to: /content/drive/MyDrive/DP_data/adpocia3.tsv\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\n"
          ]
        }
      ]
    }
  ],
  "metadata": {
    "accelerator": "GPU",
    "colab": {
      "gpuType": "T4",
      "provenance": []
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}