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license: cc-by-nc-4.0 |
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language: |
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- ja |
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- en |
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A Japanese transcription/diarization pipeline with Pyannote and Whisper large-v2 that uses a custom-tuned segmentation model and custom filtering on the audio (low-pass filter, equalizer, etc.) for improved performance. |
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Can be given a video file or mp3/wav file. |
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Performance is considerably better than default JP whisper for most tasks involving Japanese content, with the exception of singing/karaoke (Where performance is below the original due to the training dataset.) |
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Requires ffmpeg, openai-whisper, pyannote and facebookresearch's demux model. Cuda is also strongly encouraged. |
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Pyannote requies a Huggingface API key, which it will currently look for under the environment variable "HF_TOKEN_NOT_LOGIN" (At the time of this writing, naming your HF token "HF_TOKEN" causes bugs.) |
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Originally intended as a solo project, but I'm upping it here in the hopes it will be useful to practicioners. If you're doing work in this space please feel free to reach out. |
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