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---
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}
}
``` |