Zero-Shot Cross-Lingual NER Using Phonemic Representations for Low-Resource Languages
<|reference_start|>Zero-Shot Cross-Lingual NER Using Phonemic Representations for Low-Resource Languages: 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 F-1 score (46.38%) and lowest standard deviation (12.67), particularly demonstrating its robustness with non-Latin scripts.<|reference_end|>
@article{sohn2024zero-shot,
    title={Zero-Shot Cross-Lingual NER Using Phonemic Representations for
  Low-Resource Languages},
    author={Jimin Sohn, Haeji Jung, Alex Cheng, Jooeon Kang, Yilin Du, David R.
  Mortensen},
    journal={arXiv preprint arXiv:2406.16030},
    year={2024},
    archivePrefix={arXiv},
    eprint={2406.16030},
    primaryClass={cs.CL cs.AI}
}