Speaker Diarization Community 1 is a model hosted on Hugging Face for speaker diarization. It forms part of the pyannote.audio library and addresses the task of determining who spoke when in an audio recording.
The model is provided under the cc-by-4.0 license. It is listed alongside capabilities in automatic speech recognition, speaker change detection, voice activity detection, and overlapped speech detection. Four papers are referenced via arxiv links.
It is delivered as a downloadable model that loads directly into Python code through the pyannote.audio package. Inference runs on a complete audio file or on a selected time segment. The latter is performed by first cropping the waveform with the Audio utility and then passing the resulting dictionary containing waveform and sample rate to the loaded pipeline.
The model card supplies example code for both full-file and excerpt-based inference. It is intended for use in research and development involving speech and audio processing.
Speaker Diarization Community 1 sits in PulseGate's Voice, TTS & speech category. It focuses on identifying and segmenting speakers in audio recordings without manual intervention. It is built as an open-source project for audio researchers and developers. Speaker Diarization Community 1 is open source under the Open Source license. It runs on the command line.
pyannote builds and maintains Speaker Diarization Community 1, and the product first shipped in 2022. Key capabilities include speaker diarization, speaker change detection, and voice activity detection.
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pyannote/speaker-diarization-community-1 verified by the PulseGate indexer
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