Quentin Fuxa 83d0fa3fac feat: benchmark suite with WER, timestamp accuracy, cross-backend comparison ...

- Extend test_backend_offline.py with WER and timestamp accuracy metrics
  computed via whisperlivekit.metrics against ground truth transcripts.
- Add --benchmark flag to auto-detect all installed backends and run
  each (backend, policy) combination in sequence.
- Add --policy flag to override the streaming policy.
- Add detect_available_backends() probing faster-whisper, mlx-whisper,
  voxtral-mlx, voxtral (HF), and openai-whisper.
- Add print_cross_backend_comparison() with per-combo averages.
- Add run_benchmark.py for comprehensive multi-model benchmarking.
- Add BENCHMARK.md with full results on Apple M4: speed, WER,
  timestamp accuracy, VAC impact, and recommendations.
- Add ground truth transcript JSON files for all audio test files.

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..

00_00_07_english_1_speaker.transcript.json

feat: benchmark suite with WER, timestamp accuracy, cross-backend comparison

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00_00_16_french_1_speaker.transcript.json

feat: benchmark suite with WER, timestamp accuracy, cross-backend comparison

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00_00_30_english_3_speakers.transcript.json

feat: benchmark suite with WER, timestamp accuracy, cross-backend comparison

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generate_transcripts.py

feat: benchmark suite with WER, timestamp accuracy, cross-backend comparison

2026-02-22 23:27:50 +01:00