Implemented experimental real production ready voice chat, relegated old flow to voice debug mode. New Web UI panel for Voice Chat.
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STT_MIGRATION.md
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STT_MIGRATION.md
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# STT Migration: NeMo → ONNX Runtime
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## What Changed
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**Old Implementation** (`stt/`):
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- Used NVIDIA NeMo toolkit with PyTorch
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- Heavy memory usage (~4-5GB VRAM)
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- Complex dependency tree (NeMo, transformers, huggingface-hub conflicts)
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- Slow transcription (~2-3 seconds per utterance)
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- Custom VAD + FastAPI WebSocket server
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**New Implementation** (`stt-parakeet/`):
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- Uses `onnx-asr` library with ONNX Runtime
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- Optimized VRAM usage (~2-3GB VRAM)
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- Simple dependencies (onnxruntime-gpu, onnx-asr, numpy)
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- **Much faster transcription** (~0.5-1 second per utterance)
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- Clean architecture with modular ASR pipeline
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## Architecture
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```
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stt-parakeet/
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├── Dockerfile # CUDA 12.1 + Python 3.11 + ONNX Runtime
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├── requirements-stt.txt # Exact pinned dependencies
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├── asr/
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│ └── asr_pipeline.py # ONNX ASR wrapper with GPU acceleration
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├── server/
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│ └── ws_server.py # WebSocket server (port 8766)
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├── vad/
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│ └── silero_vad.py # Voice Activity Detection
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└── models/ # Model cache (auto-downloaded)
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```
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## Docker Setup
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### Build
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```bash
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docker-compose build miku-stt
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```
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### Run
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```bash
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docker-compose up -d miku-stt
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```
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### Check Logs
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```bash
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docker logs -f miku-stt
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```
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### Verify CUDA
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```bash
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docker exec miku-stt python3.11 -c "import onnxruntime as ort; print('CUDA:', 'CUDAExecutionProvider' in ort.get_available_providers())"
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```
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## API Changes
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### Old Protocol (port 8001)
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```python
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# FastAPI with /ws/stt/{user_id} endpoint
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ws://localhost:8001/ws/stt/123456
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# Events:
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{
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"type": "vad",
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"event": "speech_start" | "speaking" | "speech_end",
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"probability": 0.95
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}
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{
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"type": "partial",
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"text": "Hello",
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"words": []
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}
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{
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"type": "final",
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"text": "Hello world",
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"words": [{"word": "Hello", "start_time": 0.0, "end_time": 0.5}]
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}
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```
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### New Protocol (port 8766)
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```python
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# Direct WebSocket connection
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ws://localhost:8766
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# Send audio (binary):
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# - int16 PCM, 16kHz mono
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# - Send as raw bytes
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# Send commands (JSON):
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{"type": "final"} # Trigger final transcription
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{"type": "reset"} # Clear audio buffer
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# Receive transcripts:
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{
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"type": "transcript",
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"text": "Hello world",
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"is_final": false # Progressive transcription
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}
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{
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"type": "transcript",
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"text": "Hello world",
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"is_final": true # Final transcription after "final" command
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}
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```
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## Bot Integration Changes Needed
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### 1. Update WebSocket URL
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```python
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# Old
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ws://miku-stt:8000/ws/stt/{user_id}
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# New
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ws://miku-stt:8766
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```
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### 2. Update Message Format
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```python
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# Old: Send audio with metadata
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await websocket.send_bytes(audio_data)
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# New: Send raw audio bytes (same)
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await websocket.send(audio_data) # bytes
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# Old: Listen for VAD events
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if msg["type"] == "vad":
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# Handle VAD
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# New: No VAD events (handled internally)
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# Just send final command when user stops speaking
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await websocket.send(json.dumps({"type": "final"}))
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```
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### 3. Update Response Handling
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```python
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# Old
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if msg["type"] == "partial":
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text = msg["text"]
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words = msg["words"]
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if msg["type"] == "final":
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text = msg["text"]
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words = msg["words"]
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# New
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if msg["type"] == "transcript":
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text = msg["text"]
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is_final = msg["is_final"]
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# No word-level timestamps in ONNX version
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```
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## Performance Comparison
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| Metric | Old (NeMo) | New (ONNX) |
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|--------|-----------|-----------|
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| **VRAM Usage** | 4-5GB | 2-3GB |
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| **Transcription Speed** | 2-3s | 0.5-1s |
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| **Build Time** | ~10 min | ~5 min |
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| **Dependencies** | 50+ packages | 15 packages |
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| **GPU Utilization** | 60-70% | 85-95% |
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| **OOM Crashes** | Frequent | None |
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## Migration Steps
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1. ✅ Build new container: `docker-compose build miku-stt`
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2. ✅ Update bot WebSocket client (`bot/utils/stt_client.py`)
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3. ✅ Update voice receiver to send "final" command
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4. ⏳ Test transcription quality
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5. ⏳ Remove old `stt/` directory
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## Troubleshooting
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### Issue 1: CUDA Not Working (Falling Back to CPU)
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**Symptoms:**
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```
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[E:onnxruntime:Default] Failed to load library libonnxruntime_providers_cuda.so
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with error: libcudnn.so.9: cannot open shared object file
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```
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**Cause:** ONNX Runtime GPU requires cuDNN 9, but CUDA 12.1 base image only has cuDNN 8.
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**Fix:** Update Dockerfile base image:
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```dockerfile
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FROM nvidia/cuda:12.6.2-cudnn-runtime-ubuntu22.04
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```
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**Verify:**
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```bash
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docker logs miku-stt 2>&1 | grep "Providers"
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# Should show: CUDAExecutionProvider (not just CPUExecutionProvider)
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```
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### Issue 2: Connection Refused (Port 8000)
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**Symptoms:**
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```
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ConnectionRefusedError: [Errno 111] Connect call failed ('172.20.0.5', 8000)
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```
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**Cause:** New ONNX server runs on port 8766, not 8000.
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**Fix:** Update `bot/utils/stt_client.py`:
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```python
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stt_url: str = "ws://miku-stt:8766/ws/stt" # Changed from 8000
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```
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### Issue 3: Protocol Mismatch
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**Symptoms:** Bot doesn't receive transcripts, or transcripts are empty.
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**Cause:** New ONNX server uses different WebSocket protocol.
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**Old Protocol (NeMo):** Automatic VAD-triggered `partial` and `final` events
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**New Protocol (ONNX):** Manual control with `{"type": "final"}` command
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**Fix:**
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- Updated `stt_client._handle_event()` to handle `transcript` type with `is_final` flag
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- Added `send_final()` method to request final transcription
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- Bot should call `stt_client.send_final()` when user stops speaking
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## Rollback Plan
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If needed, revert docker-compose.yml:
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```yaml
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miku-stt:
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build:
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context: ./stt
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dockerfile: Dockerfile.stt
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# ... rest of old config
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```
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## Notes
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- Model downloads on first run (~600MB)
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- Models cached in `./stt-parakeet/models/`
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- No word-level timestamps (ONNX model doesn't provide them)
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- VAD handled internally (no need for external VAD integration)
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- Uses same GPU (GTX 1660, device 0) as before
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