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Speaker Clustering Methods

Name: Speaker Clustering Methods
Author: benchflow-ai

by benchflow-ai890173GitHub

Choose and implement clustering algorithms for grouping speaker embeddings after VAD and embedding extraction. Compare Hierarchical clustering (auto-tunes speaker count), KMeans (fast, requires known count), and Agglomerative clustering (fixed clusters). Use Hierarchical clustering when speaker count is unknown, KMeans when count is known, and always normalize embeddings before clustering.

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SKILL.md

Speaker Clustering Methods

After extracting speaker embeddings from audio segments, you need to cluster them to identify unique speakers. Different clustering methods have different strengths.

Source: https://github.com/benchflow-ai/SkillsBench#tasks_no_script_no_ref-speaker-diarization-subtitles-environment-skills-speaker-clustering

Content curated from original sources, copyright belongs to authors

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