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Merge pull request #246 from m-bain/v3

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V3
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Max Bain
2023-05-13 12:18:09 +01:00
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@ -32,12 +32,12 @@
<!-- <h2 align="left", id="what-is-it">What is it 🔎</h2> -->
This repository provides fast automatic speaker recognition (70x realtime with large-v2) with word-level timestamps and speaker diarization.
This repository provides fast automatic speech recognition (70x realtime with large-v2) with word-level timestamps and speaker diarization.
- ⚡️ Batched inference for 70x realtime transcription using whisper large-v2
- 🪶 [faster-whisper](https://github.com/guillaumekln/faster-whisper) backend, requires <8GB gpu memory for large-v2 with beam_size=5
- 🎯 Accurate word-level timestamps using wav2vec2 alignment
- 👯‍♂️ Multispeaker ASR using speaker diarization from [pyannote-audio](https://github.com/pyannote/pyannote-audio) (labels each segment/word with speaker ID)
- 👯‍♂️ Multispeaker ASR using speaker diarization from [pyannote-audio](https://github.com/pyannote/pyannote-audio) (speaker ID labels)
- 🗣️ VAD preprocessing, reduces hallucination & batching with no WER degradation
@ -74,9 +74,9 @@ GPU execution requires the NVIDIA libraries cuBLAS 11.x and cuDNN 8.x to be inst
### 2. Install PyTorch2.0, e.g. for Linux and Windows CUDA11.7:
`pip3 install torch torchvision torchaudio`
`conda install pytorch==2.0.0 torchvision==0.15.0 torchaudio==2.0.0 pytorch-cuda=11.7 -c pytorch -c nvidia`
See other methods [here.](https://pytorch.org/get-started/locally/)
See other methods [here.](https://pytorch.org/get-started/previous-versions/#v200)
### 3. Install this repo