thomasmol/whisper-diarization 🖼️📝✓🔢 → ❓

▶️ 8.7M runs 📅 Mar 2023 ⚙️ Cog 0.20.0 🔗 GitHub ⚖️ License
speaker-diarization speech-to-text

Performance

52.0sTypical run time
~110sCold start (first call)
8.7MTotal runs

About

⚡️ Blazing fast audio transcription with speaker diarization | Whisper Large V3 Turbo & pyannote 4.0 community-1 | word & sentence level timestamps | prompt

Example Output

Prompt:

"LLama, AI, Meta."

Output

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is a big part of that.","start":15.2,"words":[{"end":15.68,"word":" So","start":15.2,"speaker":"SPEAKER_01","probability":0.98681640625},{"end":16.08,"word":" Meta","start":15.68,"speaker":"SPEAKER_01","probability":0.681884765625},{"end":16.3,"word":" is","start":16.08,"speaker":"SPEAKER_01","probability":0.998046875},{"end":16.38,"word":" a","start":16.3,"speaker":"SPEAKER_01","probability":0.9990234375},{"end":16.52,"word":" big","start":16.38,"speaker":"SPEAKER_01","probability":0.99853515625},{"end":16.76,"word":" part","start":16.52,"speaker":"SPEAKER_01","probability":0.99951171875},{"end":16.86,"word":" of","start":16.76,"speaker":"SPEAKER_01","probability":0.99853515625},{"end":17.06,"word":" that.","start":16.86,"speaker":"SPEAKER_01","probability":0.99951171875}],"speaker":"SPEAKER_01","duration":1.8599999999999992,"avg_logprob":-0.17070312313735486},{"end":21.94,"text":"Meta has developed LLAMA, which is a 65 billion parameter 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Performance Metrics

52.01s Prediction Time
109.64s Total Time
All Input Parameters
{
  "file": "https://replicate.delivery/pbxt/JcL0ttZLlbchC0tL9ZtB20phzeXCSuMm0EJNdLYElgILoZci/AI%20should%20be%20open-sourced.mp3",
  "prompt": "LLama, AI, Meta.",
  "file_url": "",
  "language": "en",
  "translate": false,
  "num_speakers": 2
}
Input Parameters
file Type: stringDefault: null
Or an audio file
prompt Type: stringDefault: null
Vocabulary: provide names, acronyms and loanwords in a list. Use punctuation for best accuracy.
file_url Type: stringDefault: null
Or provide: A direct audio file URL
language Type: stringDefault: null
Language of the spoken words as a language code like 'en'. Leave empty to auto detect language.
translate Type: booleanDefault: false
Translate the speech into English.
file_string Type: stringDefault: null
Either provide: Base64 encoded audio file,
num_speakers Type: integerDefault: nullRange: 1 - 50
Number of speakers, leave empty to autodetect.
Output Schema
language Type: string
Language
segments Type: arrayItems: object
Segments
num_speakers Type: integer
Num Speakers
Example Execution Logs
/src/predict.py:233: UserWarning: torchaudio._backend.utils.info has been deprecated. This deprecation is part of a large refactoring effort to transition TorchAudio into a maintenance phase. The decoding and encoding capabilities of PyTorch for both audio and video are being consolidated into TorchCodec. Please see https://github.com/pytorch/audio/issues/3902 for more information. It will be removed from the 2.9 release. 
  metadata = torchaudio.info(str(path))
/root/.pyenv/versions/3.11.13/lib/python3.11/site-packages/torchaudio/_backend/ffmpeg.py:20: UserWarning: torio.io._streaming_media_decoder.StreamingMediaDecoder has been deprecated. This deprecation is part of a large refactoring effort to transition TorchAudio into a maintenance phase. The decoding and encoding capabilities of PyTorch for both audio and video are being consolidated into TorchCodec. Please see https://github.com/pytorch/audio/issues/3902 for more information. It will be removed from the 2.9 release. 
  s = torchaudio.io.StreamReader(src, format, None, buffer_size)
/root/.pyenv/versions/3.11.13/lib/python3.11/site-packages/torchaudio/_backend/ffmpeg.py:27: UserWarning: torchaudio._backend.common.AudioMetaData has been deprecated. This deprecation is part of a large refactoring effort to transition TorchAudio into a maintenance phase. The decoding and encoding capabilities of PyTorch for both audio and video are being consolidated into TorchCodec. Please see https://github.com/pytorch/audio/issues/3902 for more information. It will be removed from the 2.9 release. 
  return AudioMetaData(
INFO:predict:Audio metadata: sample_rate=44100, num_channels=2, num_frames=66473984, bits_per_sample=0, encoding=MP3
INFO:predict:Audio normalized in 3.02s
INFO:predict:Audio duration: 1507.35s
INFO:predict:GPU type: NVIDIA L40S
INFO:predict:Starting transcription
INFO:faster_whisper:Processing audio with duration 25:07.347
INFO:faster_whisper:VAD filter removed 00:37.899 of audio
INFO:predict:Transcription completed in 28.72s. Detected language: en. Segments: 908
INFO:predict:Starting diarization
/root/.pyenv/versions/3.11.13/lib/python3.11/site-packages/torchaudio/_backend/utils.py:213: UserWarning: In 2.9, this function's implementation will be changed to use torchaudio.load_with_torchcodec` under the hood. Some parameters like ``normalize``, ``format``, ``buffer_size``, and ``backend`` will be ignored. We recommend that you port your code to rely directly on TorchCodec's decoder instead: https://docs.pytorch.org/torchcodec/stable/generated/torchcodec.decoders.AudioDecoder.html#torchcodec.decoders.AudioDecoder.
  warnings.warn(
/root/.pyenv/versions/3.11.13/lib/python3.11/site-packages/torchaudio/_backend/ffmpeg.py:88: UserWarning: torio.io._streaming_media_decoder.StreamingMediaDecoder has been deprecated. This deprecation is part of a large refactoring effort to transition TorchAudio into a maintenance phase. The decoding and encoding capabilities of PyTorch for both audio and video are being consolidated into TorchCodec. Please see https://github.com/pytorch/audio/issues/3902 for more information. It will be removed from the 2.9 release. 
  s = torchaudio.io.StreamReader(src, format, None, buffer_size)
/root/.pyenv/versions/3.11.13/lib/python3.11/site-packages/pyannote/audio/utils/reproducibility.py:74: ReproducibilityWarning: TensorFloat-32 (TF32) has been disabled as it might lead to reproducibility issues and lower accuracy.
It can be re-enabled by calling
   >>> import torch
   >>> torch.backends.cuda.matmul.allow_tf32 = True
   >>> torch.backends.cudnn.allow_tf32 = True
See https://github.com/pyannote/pyannote-audio/issues/1370 for more details.

  warnings.warn(
/root/.pyenv/versions/3.11.13/lib/python3.11/site-packages/pyannote/audio/models/blocks/pooling.py:103: UserWarning: std(): degrees of freedom is <= 0. Correction should be strictly less than the reduction factor (input numel divided by output numel). (Triggered internally at /pytorch/aten/src/ATen/native/ReduceOps.cpp:1839.)
  std = sequences.std(dim=-1, correction=1)
INFO:predict:Diarization completed in 15.41s. Detected speakers: 2
INFO:predict:Starting segment reconciliation
INFO:predict:Segment reconciliation completed in 2.45s. Final segments: 217
INFO:predict:Run completed in 51.31s
Version Details
Version ID
744c4f2bffae674f82e79ed46f9cc54796d4903b3e20e68353e05a93eb10a55c
Version Created
June 10, 2026
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