# ADR 0003: Use pyannote for Speaker Diarization

## Status

Accepted, amended by [ADR 0011](0011-use-meeting-lab-mvp-backend.md)

## Context

The project requires speaker diarization to assign transcript segments to speakers.

The first implementation should provide reliable separation of speakers in meetings, while keeping the diarization component replaceable.

## Decision

The project will use `pyannote.audio` as the initial speaker diarization engine.

Speaker diarization will be treated as a separate pipeline step after transcription.

## Consequences

- Diarization can be improved or replaced independently from transcription.
- Speaker labels are derived metadata and must not modify the canonical transcript.
- Human correction of speaker names should be supported later.
- The diarization module must hide the concrete engine behind an internal interface.
- Model name, engine version and timestamp should be stored with every diarization result.

## Amendment

ADR 0011 makes diarization optional for the MVP and selects `pyannote.audio`
Community-1 as the current preferred backend. CPU execution remains supported,
with GPU acceleration used when available. Speaker labels remain anonymous
unless a user explicitly confirms a `SPEAKER_XX` to participant mapping in the
Meeting Context. Automatic speaker-name inference is not allowed.