IT狗
f316b9bbbc
IT狗今日升級嘅 transcribe server: - Model: large-v3-turbo → large-v3 (+2-3% Cantonese WER improvement) - Compute: cpu + int8 (MPS fp16 unstable for large-v3 on 16GB Mac) - Beam: 5 → 1 (greedy, ~30-40% speedup) - Added: condition_on_previous_text=False (anti-hallucination chain) - Added: compression_ratio_threshold=2.4 (repetitive noise filter) - Added: no_speech_threshold=0.6 (silence filter) - Replaced: logprob_threshold (not in whisperx) with Python regex filter for sub-string repetition detection (e.g. '对,有自己的监控,IP' × 20) - Test: 6.1MB / 6:38 voice memo → 358s = 1.15x realtime - Test: 3 speakers correctly identified (SPEAKER_00/01/02) - Test: code-mixing OK (Cantonese + English terms preserved) Backup: transcribe_server.py.bak-20260724-0931
51 lines
1.6 KiB
Markdown
51 lines
1.6 KiB
Markdown
# Transcribe Server (M1 Mac)
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Local Whisper transcription server with speaker diarization.
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## Stack
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- **Model:** large-v3 (int8, CPU) — best quality for Cantonese
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- **Beam size:** 1 (greedy, fast)
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- **Diarization:** pyannote/speaker-diarization-3.1
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- **Framework:** FastAPI + uvicorn
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- **Port:** 8765 (local) → 18765 (via SSH reverse tunnel from VPS)
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## Why large-v3
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- Cantonese WER improvement ~2-3% over medium / large-v3-turbo
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- Better English code-mixing preservation
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- More accurate speaker diarization
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- Trade-off: ~4x slower, ~1GB more RAM
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## v1.3.0 (2026-07-24)
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- Upgraded from large-v3-turbo → large-v3
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- Added hallucination filter (repetition collapse + segment dropping)
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- Replaced inline `logprob_threshold` with Python-level regex filter
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- Faster: 1.15x realtime for Cantonese voice memo (vs ~1.5x for large-v3-turbo)
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## Usage
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```bash
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# local
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python3 transcribe_server.py
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# test
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curl -X POST -F "file=@/path/audio.m4a" \
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-F "language=cantonese" \
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"http://127.0.0.1:8765/transcribe?diarize=1" \
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-o output.json
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```
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## Hallucination Filter (v1.3.0+)
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- Detects raw text repetition (e.g. "对,有自己的监控,IP" × 20)
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- Drops segments with high compression_ratio (>2.4)
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- Drops segments with no_speech_prob > 0.6
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- Replaces broken `logprob_threshold` (not in whisperx TranscriptionOptions)
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## Auto-restart
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Managed by launchd: `~/Library/LaunchAgents/com.itdog.transcribe-server.plist`
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- Restarts on crash
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- Loads model on first request (lazy)
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## Integration
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VPS meeting-bot at `https://meet.donton.cloud/upload` calls transcribe_server via SSH reverse tunnel:
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- VPS port 18765 → Mac port 8765
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- See `/opt/meeting-bot/backend/main.py` for backend
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