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    <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</abstract>
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%0 Conference Proceedings
%T Zero-Shot Cross-Lingual NER Using Phonemic Representations for Low-Resource Languages
%A Sohn, Jimin
%A Jung, Haeji
%A Cheng, Alex
%A Kang, Jooeon
%A Du, Yilin
%A Mortensen, David
%Y Al-Onaizan, Yaser
%Y Bansal, Mohit
%Y Chen, Yun-Nung
%S Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
%D 2024
%8 November
%I Association for Computational Linguistics
%C Miami, Florida, USA
%F sohn-etal-2024-zero
%X 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
%U https://aclanthology.org/2024.emnlp-main.753
%P 13595-13602

Markdown (Informal)

[Zero-Shot Cross-Lingual NER Using Phonemic Representations for Low-Resource Languages](https://aclanthology.org/2024.emnlp-main.753) (Sohn et al., EMNLP 2024)

• Zero-Shot Cross-Lingual NER Using Phonemic Representations for Low-Resource Languages (Sohn et al., EMNLP 2024)

ACL

• Jimin Sohn, Haeji Jung, Alex Cheng, Jooeon Kang, Yilin Du, and David Mortensen. 2024. Zero-Shot Cross-Lingual NER Using Phonemic Representations for Low-Resource Languages. In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, pages 13595–13602, Miami, Florida, USA. Association for Computational Linguistics.