@inproceedings{layacan-etal-2024-zero,
title = "Zero-shot Cross-lingual {POS} Tagging for {F}ilipino",
author = "Layacan, Jimson Paulo and
Flores, Isaiah Edri W. and
Tan, Katrina Bernice M. and
Estuar, Ma. Regina E. and
Montalan, Jann Railey E. and
De Leon, Marlene M.",
editor = "Serikov, Oleg and
Voloshina, Ekaterina and
Postnikova, Anna and
Muradoglu, Saliha and
Le Ferrand, Eric and
Klyachko, Elena and
Vylomova, Ekaterina and
Shavrina, Tatiana and
Tyers, Francis",
booktitle = "Proceedings of the Third Workshop on NLP Applications to Field Linguistics",
month = aug,
year = "2024",
address = "Bangkok, Thailand",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.fieldmatters-1.9/",
doi = "10.18653/v1/2024.fieldmatters-1.9",
pages = "69--77",
abstract = "Supervised learning approaches in NLP, exemplified by POS tagging, rely heavily on the presence of large amounts of annotated data. However, acquiring such data often requires significant amount of resources and incurs high costs. In this work, we explore zero-shot cross-lingual transfer learning to address data scarcity issues in Filipino POS tagging, particularly focusing on optimizing source language selection. Our zero-shot approach demonstrates superior performance compared to previous studies, with top-performing fine-tuned PLMs achieving F1 scores as high as 79.10{\%}. The analysis reveals moderate correlations between cross-lingual transfer performance and specific linguistic distances{--}featural, inventory, and syntactic{--}suggesting that source languages with these features closer to Filipino provide better results. We identify tokenizer optimization as a key challenge, as PLM tokenization sometimes fails to align with meaningful representations, thus hindering POS tagging performance."
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%0 Conference Proceedings
%T Zero-shot Cross-lingual POS Tagging for Filipino
%A Layacan, Jimson Paulo
%A Flores, Isaiah Edri W.
%A Tan, Katrina Bernice M.
%A Estuar, Ma. Regina E.
%A Montalan, Jann Railey E.
%A De Leon, Marlene M.
%Y Serikov, Oleg
%Y Voloshina, Ekaterina
%Y Postnikova, Anna
%Y Muradoglu, Saliha
%Y Le Ferrand, Eric
%Y Klyachko, Elena
%Y Vylomova, Ekaterina
%Y Shavrina, Tatiana
%Y Tyers, Francis
%S Proceedings of the Third Workshop on NLP Applications to Field Linguistics
%D 2024
%8 August
%I Association for Computational Linguistics
%C Bangkok, Thailand
%F layacan-etal-2024-zero
%X Supervised learning approaches in NLP, exemplified by POS tagging, rely heavily on the presence of large amounts of annotated data. However, acquiring such data often requires significant amount of resources and incurs high costs. In this work, we explore zero-shot cross-lingual transfer learning to address data scarcity issues in Filipino POS tagging, particularly focusing on optimizing source language selection. Our zero-shot approach demonstrates superior performance compared to previous studies, with top-performing fine-tuned PLMs achieving F1 scores as high as 79.10%. The analysis reveals moderate correlations between cross-lingual transfer performance and specific linguistic distances–featural, inventory, and syntactic–suggesting that source languages with these features closer to Filipino provide better results. We identify tokenizer optimization as a key challenge, as PLM tokenization sometimes fails to align with meaningful representations, thus hindering POS tagging performance.
%R 10.18653/v1/2024.fieldmatters-1.9
%U https://aclanthology.org/2024.fieldmatters-1.9/
%U https://doi.org/10.18653/v1/2024.fieldmatters-1.9
%P 69-77
Markdown (Informal)
[Zero-shot Cross-lingual POS Tagging for Filipino](https://aclanthology.org/2024.fieldmatters-1.9/) (Layacan et al., FieldMatters 2024)
ACL
- Jimson Paulo Layacan, Isaiah Edri W. Flores, Katrina Bernice M. Tan, Ma. Regina E. Estuar, Jann Railey E. Montalan, and Marlene M. De Leon. 2024. Zero-shot Cross-lingual POS Tagging for Filipino. In Proceedings of the Third Workshop on NLP Applications to Field Linguistics, pages 69–77, Bangkok, Thailand. Association for Computational Linguistics.