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Model: NUTN-KWS/Whisper-Taiwanese-model-v0.5
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---
library_name: transformers
license: cc-by-nc-4.0
language:
- en
- zh
metrics:
- cer
pipeline_tag: automatic-speech-recognition
base_model:
- openai/whisper-large-v3-turbo
---
[ [英文 README_EN.md](https://huggingface.co/NUTN-KWS/Whisper-Taiwanese-model-v0.5/blob/main/README_EN.md) ]
# 👳 Whisper-Taiwanese model V0.5 (Tv0.5)
這個模型是由國立臺南大學執行國科會產學合作計畫,使用 [openai/whisper-large-v3-turbo](https://huggingface.co/openai/whisper-large-v3-turbo) 微調的版本並執行國科會TAIDE台英語家庭先導計畫與真平出版社合作使用中小學教材內容及學生學習資料進行模型微調用於真平教材台語辨識。並與國研院國網中心合作運用國網中心算力以及TAIDE模型共同建構中小學台語AI學習模型。
示範網址: [https://kws.oaselab.org/taigitong/](https://kws.oaselab.org/taigitong/)
## 📝 Model Details
- **Base Model**: `openai/whisper-large-v3-turbo`
- **Fine-tuned for**: 台灣閩南語語音辨識 (ASR)
- **Fine-tuning Framework**: Hugging Face Transformers
- **Training Duration**: 使用兩片 V100大約 180 小時
- **Dataset**: 自訂資料集、教育部臺灣台語常用詞辭典,大約 90 小時的資料
- **Input Format**: 16kHz mono WAV
- **License**: CC BY-NC 4.0
## 🚀 Usage
### 安裝套件:
```bash
pip install torch torchvision torchaudio transformers
```
### 執行範例:
```python
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="./model/whisper-taiwanese", device=0)
result = pipe("audio.wav", generate_kwargs={"language": "zh", "task": "transcribe"})
print(result["text"])
```
## 👨‍🎓 Citation
### BibTeX:
```bibtex
@misc{taiwanesewhisperasr2025,
title={Taiwanese Whisper ASR},
author={KWS Center, National University of Tainan, Taiwan},
year={2025},
url={https://huggingface.co/NUTN-KWS/Whisper-Taiwanese-model-v0.5}
}
```
### APA:
- C. S. Lee, M. H. Wang, C. C. Yue, G. Y. Teseng, and Y. Nojima, "Fuzzy Estimation Agent with Knowledge Graph and Quantum Fuzzy Inference Engine for Taiwanese-English Co-Learning," 2025 IFSA World Congress and NAFIPS Annual Meeting (IFSA/NAFIPS 2025), Banff, Alberta, Canada, Aug. 16-19, 2025.
- C. S. Lee, M. H. Wang, C. Y. Chen, S. C. Yang, M. Reformat, N. Kubota, and A. Pourabdollah, "Integrating quantum CI and generative AI for Taiwanese/English co-learning," Quantum Machine Intelligence, vol. 6, 64, pp. 1-19, 2024.
- C. S. Lee, M. H. Wang, C. Y. Chen, S. C. Yang, M. Reformat, N. Kubota, and A. Pourabdollah, "Quantum fuzzy inference engine with generative AI and TAIDE KG for Taiwanese/English co-learning," 2025 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2025), Reims, France, Jul. 6-9, 2025.