{"id":"b321d3f1-77a9-4db0-9f76-ca95d295dd83","shortId":"uDFZZr","kind":"skill","title":"Whisper Diarization Post-Processor","tagline":"Enhances OpenAI Whisper transcription output with speaker diarization using pyannote.audio pipeline and speechbrain embeddings. Aligns word-level timestamps from whisper-timestamped with speaker segments for multi-speaker meeting transcript generation.","description":"# Whisper Diarization Post-Processor\n\nEnhances OpenAI Whisper transcription output with speaker diarization using pyannote.audio pipeline and speechbrain embeddings. Aligns word-level timestamps from whisper-timestamped with speaker segments for multi-speaker meeting transcript generation.\n\n## Installation\n\nUse the upstream install or setup path that matches your environment:\n- pip install -U openai-whisper\n- pip install git+https://github.com/openai/whisper.git\n- pip install --upgrade --no-deps --force-reinstall git+https://github.com/openai/whisper.git\n- brew install ffmpeg\n\nRequirements and caveats from upstream:\n- We used Python 3.9.9 and [PyTorch](https://pytorch.org/) 1.10.1 to train and test our models, but the codebase is expected to be compatible with Python 3.8-3.11 and recent PyTorch versions. The codebase also depends o...\n- Alternatively, the following command will pull and install the latest commit from this repository, along with its Python dependencies:\n- It also requires the command-line tool [ffmpeg](https://ffmpeg.org/) to be installed on your system, which is available from most package managers:\n\nBasic usage or getting-started notes:\n- [[Colab example]](https://colab.research.google.com/github/openai/whisper/blob/master/notebooks/LibriSpeech.ipynb)\n- To update the package to the latest version of this repository, please run:\n- bash\n\n- Source: https://github.com/openai/whisper\n- Extracted from upstream docs: https://raw.githubusercontent.com/openai/whisper/HEAD/README.md\n\n## Source\n\n- [Agent Skill 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