Speaker Diarization
Speaker Diarization is a pre-trained pipeline available on Hugging Face for determining who spoke when in an audio recording. It forms part of the pyannote.audio toolkit and addresses the task of segmenting and labeling speakers within voice recordings.
The model supports automatic speech recognition workflows through integrated capabilities for speaker diarization, voice activity detection, and overlapped speech detection. It draws on research documented in two arXiv papers from 2021 and 2020. Users invoke it via the pyannote.audio library by loading the pipeline from the repository identifier and passing either a full audio file or a cropped excerpt defined by start and end times.
Delivery occurs as a downloadable model hosted on the Hugging Face platform. The provided code examples demonstrate inference on a local WAV file or on a waveform segment extracted using the accompanying Audio utility. It is distributed under the MIT license, allowing broad reuse in research and development.
The pipeline is intended for developers and researchers working in speech processing who integrate it into local applications, notebooks, or custom audio analysis scripts.
Overview
3 featuresSpeaker Diarization is a Speech to text project. Automatically identifying and segmenting different speakers in multi-speaker audio recordings. Speaker Diarization is an open-source project aimed at developers. Speaker Diarization is open source under the MIT license. It ships for the web, the command line, and API.
pyannote builds and maintains Speaker Diarization, and it first shipped in 2016. Development happens publicly on GitHub with 10.3k stars and 13 commits in the last 90 days. Among its 3 catalogued features are speaker diarization, voice activity detection, and overlapped speech detection.
Summary written by a language model from the project’s public pages.
- Speaker diarization
- Voice activity detection
- Overlapped speech detection
Built with & integrations
- AWS
- x-amz-cf-id header · x-amz-cf-pop header · via header
- openai
- dall- in the HTML
Trust & compliance
Indexing history
1What PulseGate has recorded for this listing
- Indexed21 Jul · 17:06 UTCpyannote/speaker-diarization-3.0 verified via Hugging Face EnumeratorSource: Hugging Face Enumerator · Open
Frequently asked questions about Speaker Diarization
- What does Speaker Diarization do?
- Automatically identifying and segmenting different speakers in multi-speaker audio recordings. It is catalogued under Speech to text on PulseGate.
- Who is Speaker Diarization for?
- Speaker Diarization is an open-source project built for developers.
- Is Speaker Diarization free?
- 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 maintained?
- The GitHub repository shows 13 commits in the last 90 days.
- What projects are similar 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.
Similar projects
Closest matches by what these projects do