README.md

---
license: apache-2.0
tags:
  - automatic-speech-recognition
  - coreml
  - whisperkit
  - apple-silicon
  - asr
  - on-device
  - breeze
  - mediatek
model_type: automatic-speech-recognition
library_name: whisperkit
pipeline_tag: automatic-speech-recognition
---

# Breeze-ASR-25 CoreML

This model is based on [MediaTek-Research_Breeze-ASR-25](https://huggingface.co/MediaTek-Research/Breeze-ASR-25), a state-of-the-art automatic speech recognition (ASR) model. 
It has been converted into the CoreML format for compatibility with Whisperkit, enabling efficient ASR inference on Apple Silicon devices.

## Model Description

Breeze-ASR-25 is a high-performance automatic speech recognition model developed by MediaTek Research. This CoreML version enables on-device inference on Apple Silicon devices through Whisperkit integration.

## Model Components

This repository contains three CoreML models:

1. **AudioEncoder.mlmodelc** - Audio feature encoder
2. **MelSpectrogram.mlmodelc** - Mel spectrogram processor  
3. **TextDecoder.mlmodelc** - Text decoder for transcription

## Usage

### With Whisperkit

```python
import whisperkit

# Load the model
model = whisperkit.load_model("your-username/Breeze-ASR-25_coreml")

# Transcribe audio
result = model.transcribe("path/to/audio.wav")
print(result.text)
```

### Requirements

- macOS with Apple Silicon (M1/M2/M3)
- iOS 16.0+ or macOS 13.0+
- Whisperkit framework

## Performance

- Optimized for Apple Silicon devices
- On-device inference (no internet required)
- Low latency and memory usage
- High accuracy speech recognition

## License

This model is licensed under the Apache 2.0 License.

## Citation

If you use this model, please cite the original Breeze-ASR-25 paper:

```bibtex
@article{breeze-asr-25,
  title={Breeze-ASR-25: Efficient Speech Recognition for Mobile Devices},
  author={MediaTek Research},
  journal={arXiv preprint},
  year={2024}
}
```