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ddidderr 3042b7743b feat!: use whole-recording Pyannote speaker diarization
Sampled Gemini voice matching could leave one person under separate IDs
across transcription chunks. Use hosted Precision-2 on the complete
recording and align its exclusive speaker timeline with MAI word timing.
Preserve transcription text, order, and timestamps; leave ambiguous word
assignments unknown instead of merging identities to satisfy a count.

Upload lossless FLAC, bound polling, retry transient status reads against
the same job, and validate results before emitting stdout. Keep optional
speaker-count and hosted model overrides. Disable MAI diarization and use
30-minute transcription uploads in both modes. Respect environment keys,
keep authentication out of process arguments, and save optional diagnostics
without audio, credentials, or signed upload URLs.

Test Plan:
- python3 -B -m unittest -v: all 101 regression tests passed, including
  mocked provider upload, polling, alignment, failure, and cleanup paths.
- bash -n transcribe and shellcheck transcribe: passed.
- git diff --cached --check: passed.
- Prepared the 74-minute input locally and verified identical decoded PCM
  hashes for the normalized WAV and full-recording lossless FLAC.
- Live API testing was explicitly deferred by the user; mocked results do
  not establish speaker accuracy on the recording.

BREAKING CHANGE: Default diarization requires PYANNOTE_API_KEY or its
1Password reference. --speaker-model accepts hosted precision-2 or
community-1 instead of OpenRouter audio-chat model IDs.
2026-09-12 11:18:30 +02:00
..