This Hugging Face Space runs the Pyannote 3.1 model to perform speaker diarization on uploaded audio. It identifies distinct speakers, assigns labels, and produces both a text output and a downloadable annotated audio file. Optional speaker count input can improve accuracy.
In the AI & ML space, Pyannote Speaker Diarization 3.1 takes a focused approach. Automatically determining who spoke when in multi-speaker audio recordings. Pyannote Speaker Diarization 3.1 is a B2B2C product aimed at researchers and audio engineers. It is available for free. It ships for the web, and it can be self-hosted.
Behind Pyannote Speaker Diarization 3.1 is Delik, and it first shipped in 2024. Among its 3 catalogued features are Speaker Diarization, Audio Analysis, and Speaker Labeling.
Summary written by a language model from the project’s public pages.
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