Data Science & Analytics

Speaker Clustering Methods

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.

Publisher / source

benchflow-ai/skillsbench (found on GitHub top repositories)

Upstream record

benchflow-ai/skillsbench

Version

Version 1

Published

2026-11-08

Publication review

Approved for publication · recorded passed scan 2026-11-08

Content fingerprint

915873f13e7c2c9b3f8c87db06fb2332cb3941ccb70b49397b224173121990d1