Speaker Diarization
Speaker Diarization 3.1 is a pre-trained pipeline published on Hugging Face that performs speaker diarization on audio recordings. It identifies which speaker spoke when by combining voice activity detection, speaker change detection, and overlapped speech detection.
The model is provided by pyannote and is based on the pyannote.audio library. It accepts full audio files or cropped excerpts supplied as waveform and sample rate. Inference returns annotated segments that assign speaker labels to portions of the input. The pipeline is delivered as a downloadable model from the Hugging Face hub and runs locally through the pyannote.audio Python library. Example code demonstrates loading the pipeline and processing either an entire WAV file or a defined time segment.
It carries an MIT license. The associated research appears in two arXiv papers referenced on the model card. Notebooks for Google Colab and Kaggle are linked to support experimentation. The model page classifies the work under automatic speech recognition and lists tags for audio, voice, speech, speaker diarization, speaker change detection, voice activity detection, and overlapped speech detection.
Overview
4 featuresSpeaker Diarization is a Speech to text project. It focuses on determining which speaker said what and when in multi-speaker audio recordings. It is built as an open-source project for machine learning developers. Speaker Diarization is open source under the MIT license. It runs on the web, the command line, and API.
It is developed by pyannote, and it first shipped in 2016. Development happens publicly on GitHub with 10.3k stars and 13 commits in the last 90 days. Key capabilities include Speaker Diarization, Voice Activity Detection, and Overlapped Speech Detection. It exposes integrations via a public API.
Summary written by a language model from the project’s public pages.
- Speaker Diarization
- Voice Activity Detection
- Overlapped Speech Detection
- Pyannote Pipeline
Built with & integrations
- AWS
- x-amz-cf-id header · x-amz-cf-pop header · via header
Trust & compliance
Indexing history
1What PulseGate has recorded for this listing
- Indexed20 Jul · 20:04 UTCpyannote/speaker-diarization-3.1 verified via Hugging Face EnumeratorSource: Hugging Face Enumerator · Open
Frequently asked questions about Speaker Diarization
- What does Speaker Diarization do?
- Speaker Diarization focuses on determining which speaker said what and when in multi-speaker audio recordings. It is catalogued under Speech to text on PulseGate.
- Who should use Speaker Diarization?
- Speaker Diarization is an open-source project built for machine learning developers.
- Does Speaker Diarization have a free plan?
- Yes — Speaker Diarization is open source under the MIT license and free to use.
- What platforms does Speaker Diarization run on?
- Speaker Diarization runs on the web, the command line, and API.
- Is Speaker Diarization still active?
- The GitHub repository shows 13 commits in the last 90 days.
- What are alternatives to Speaker Diarization?
- Similar projects tracked by PulseGate include Speaker Diarization, Speaker Diarization Community 1, and Speaker Diarization Community 1.Speaker DiarizationSpeaker Diarization Community 1Speaker Diarization Community 1
- Who develops Speaker Diarization?
- Speaker Diarization is developed by pyannote.
- How long has Speaker Diarization been around?
- Speaker Diarization first shipped in 2016.
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