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# REX Wake-Word Models

Custom wake-word models for the [REX voice assistant](https://github.com/David-Antolick/rex_voice_assistant).

## Models

- **hey_rex.onnx** - openWakeWord model for the phrase "hey rex".
- **hey_rex.tflite** - same model, TFLite runtime version.

Trained with the openWakeWord automatic training pipeline:
- 2000 Piper TTS synthetic positives + 329 real recordings from 3 speakers
- Background data: FMA music + ACAV100M precomputed features (~2000 hrs)
- 10,000 training steps on an RTX 3070 Ti

## Usage

REX 0.3.2+ downloads this model automatically when wake-word gating is enabled.

For direct use with openWakeWord:

```python
from openwakeword.model import Model
oww = Model(wakeword_models=["hey_rex.onnx"], inference_framework="onnx")
score = oww.predict(audio_int16_chunk_1280_samples)["hey_rex"]
```

Audio format: 16 kHz mono int16, fed in chunks of 1280 samples (80 ms).
Default detection threshold: 0.5 (raise to ~0.7 to reduce false fires).

## License

MIT, matching the REX project. Voice samples used in training were collected
with explicit consent from contributors for inclusion in this model and its
distribution (including any commercial distribution, though none is intended).