wq2012/SpectralCluster
Python re-implementation of the (constrained) spectral clustering algorithms used in Google's speaker diarization papers.
This tool helps you group audio segments by speaker, a process known as speaker diarization. It takes in numerical representations of sound (audio embeddings) and outputs labels indicating which speaker is talking at different times. An audio engineer, researcher, or anyone working with multi-speaker audio recordings would use this to identify and separate individual voices.
546 stars. No commits in the last 6 months. Available on PyPI.
Use this if you need to determine "who spoke when" in an audio recording, given pre-computed numerical embeddings of the audio.
Not ideal if you need a complete, production-ready speaker diarization system that handles audio input directly, as this tool focuses specifically on the clustering step.
Stars
546
Forks
73
Language
Python
License
Apache-2.0
Category
Last pushed
Sep 25, 2024
Commits (30d)
0
Dependencies
3
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