LULab/

whisper-openNMT-Synde-version-without-features-synthetic-data

@inproceedings{lin2025aec,
title={ASR Error Correction in Low-Resource Burmese with Alignment-Enhanced Transformers using Phonetic Features},
author={Lin, Ye Bhone and Aung, Thura and Thu, Ye Kyaw and Oo, Thazin Myint},
booktitle={2025 20th International Joint Symposium on Artificial Intelligence and Natural Language Processing (iSAI-NLP)},
pages={1--6},
year={2025},
keywords={Burmese language; Automatic Speech Recognition; ASR Error Correction; IPA; Alignment; Transformer},
location={Phuket, Thailand}
}