Zero-Shot Cross-Lingual NER Using Phonemic Representations for Low-Resource Languages
Jimin Sohn, Haeji Jung, Alex Cheng, Jooeon Kang, Yilin Du, David R Mortensen
Abstract
Existing zero-shot cross-lingual NER approaches require substantial prior knowledge of the target language, which is impractical for low-resource languages.In this paper, we propose a novel approach to NER using phonemic representation based on the International Phonetic Alphabet (IPA) to bridge the gap between representations of different languages.Our experiments show that our method significantly outperforms baseline models in extremely low-resource languages, with the highest average F1 score (46.38%) and lowest standard deviation (12.67), particularly demonstrating its robustness with non-Latin scripts. Ourcodes are available at https://github.com/Gabriel819/zeroshot_ner.git
BibTeX
@inproceedings{sohn-etal-2024-zero,
title = "Zero-Shot Cross-Lingual {NER} Using Phonemic Representations for Low-Resource Languages",
author = "Sohn, Jimin and
Jung, Haeji and
Cheng, Alex and
Kang, Jooeon and
Du, Yilin and
Mortensen, David R",
editor = "Al-Onaizan, Yaser and
Bansal, Mohit and
Chen, Yun-Nung",
booktitle = "Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing",
month = nov,
year = "2024",
address = "Miami, Florida, USA",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.emnlp-main.753/",
doi = "10.18653/v1/2024.emnlp-main.753",
pages = "13595--13602"
}