Individual skill
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.
tasks-extra/speaker-diarization-subtitles/environment/skills/speaker-clustering/SKILL.md
Source commit f860ecf02ef53412a030f8661c83d644b739ff01
What was checked
- Matches the observed repository HEAD
- Yes
- Scanner rules are current
- No
- Repository scan complete
- No
- Skill scan complete
- No
- Observed behavior
- Not checked yet
- Last checked
- Nov 3, 2026
These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.
Install this skill
Choose an agent in your Stack or copy a command below. Commands fetch the pinned commit and copy only this skill directory. Existing destinations are refused. Copying a command does not install anything.
Standard SKILL.md format has not been attested at this commit. No installation command is available; inspect the source.
Repository context
- Repository stars (not skill ratings)
- 1,906
- Repository last updated
- Nov 4, 2026
- License
- Apache-2.0
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
- benchmark Repository topic
- skillsbench Repository topic
- engineering Derived category
Files and excerpt
File metadata and permitted, redacted excerpts come from the recorded scan. Source links are pinned to that commit.
Browse files
Read excerpt
# Speaker Clustering Methods
## Overview
After extracting speaker embeddings from audio segments, you need to cluster them to identify unique speakers. Different clustering methods have different strengths.
## When to Use
- After extracting speaker embeddings from VAD segments
- Need to group similar speakers together
- Determining number of speakers automatically or manually
## Available Clustering Methods
