Zero-Shot Cross-Lingual NER Using Phonemic Representations for Low-Resource Languages
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arXiv
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| Autores principales: | , , , , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| Acceso en línea: | |
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| _version_ | 1866910659228205056 |
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| author | Sohn, Jimin Jung, Haeji Cheng, Alex Kang, Jooeon Du, Yilin Mortensen, David R. |
| author_facet | Sohn, Jimin Jung, Haeji Cheng, Alex Kang, Jooeon Du, Yilin Mortensen, David R. |
| contents | 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. Our codes are available at https://github.com/Gabriel819/zeroshot_ner.git |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_16030 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Zero-Shot Cross-Lingual NER Using Phonemic Representations for Low-Resource Languages Sohn, Jimin Jung, Haeji Cheng, Alex Kang, Jooeon Du, Yilin Mortensen, David R. Computation and Language Artificial Intelligence 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. Our codes are available at https://github.com/Gabriel819/zeroshot_ner.git |
| title | Zero-Shot Cross-Lingual NER Using Phonemic Representations for Low-Resource Languages |
| topic | Computation and Language Artificial Intelligence |
| url | https://arxiv.org/abs/2406.16030 |