Subtitle

Speaker Diarization

Automatically identify, separate, and label different speakers within an audio or video track for accurate attribution.

Overview

How it helps

Automatically identify, separate, and label different speakers within an audio or video track for accurate attribution.

Capabilities

Detects speaker changes based on voice characteristics
Clusters audio segments by distinct speaker identity
Assigns consistent speaker labels across the timeline
Supports multi-speaker discussions and panels
Integrates with subtitle and transcription workflows
Runs fully offline with deterministic behavior

Use Cases

Labeling speakers in interviews and podcasts

Attributing dialogue correctly in multi-speaker videos

Improving subtitle readability and structure

Supporting downstream translation and editing workflows

Ready to streamline subtitle workflows?

  • Deterministic output ensuring synchronization
  • Professional-grade timing and formatting
  • Significantly reduced post-editing time