@inproceedings{meyers-etal-2025-role,
title = "The Role of Handling Attributive Nouns in Improving {C}hinese-To-{E}nglish Machine Translation",
author = "Meyers, Adam and
Zevallos, Rodolfo Joel and
Ortega, John E. and
Wang, Lisa",
editor = "Sharoff, Serge and
Terryn, Ayla Rigouts and
Zweigenbaum, Pierre and
Rapp, Reinhard",
booktitle = "Proceedings of the 18th Workshop on Building and Using Comparable Corpora (BUCC)",
month = jan,
year = "2025",
address = "Abu Dhabi, UAE",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.bucc-1.7/",
pages = "57--61",
abstract = "Translating between languages with drastically different grammatical conventions poses significant challenges, not just for human interpreters but also for machine translation systems. In this work, we specifically target the translation challenges posed by attributive nouns in Chinese, which frequently cause ambiguities in English translation. By manually inserting the omitted particle {\textquoteleft}DE' in news article titles from the Penn Chinese Discourse Treebank, we developed a targeted dataset to fine-tune Hugging Face Chinese to English translation models, specifically improving how this critical function word is handled. This focused approach not only complements the broader strategies suggested by previous studies but also offers a practical enhancement by specifically addressing a common error type in Chinese-English translation."
}
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<abstract>Translating between languages with drastically different grammatical conventions poses significant challenges, not just for human interpreters but also for machine translation systems. In this work, we specifically target the translation challenges posed by attributive nouns in Chinese, which frequently cause ambiguities in English translation. By manually inserting the omitted particle ‘DE’ in news article titles from the Penn Chinese Discourse Treebank, we developed a targeted dataset to fine-tune Hugging Face Chinese to English translation models, specifically improving how this critical function word is handled. This focused approach not only complements the broader strategies suggested by previous studies but also offers a practical enhancement by specifically addressing a common error type in Chinese-English translation.</abstract>
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%0 Conference Proceedings
%T The Role of Handling Attributive Nouns in Improving Chinese-To-English Machine Translation
%A Meyers, Adam
%A Zevallos, Rodolfo Joel
%A Ortega, John E.
%A Wang, Lisa
%Y Sharoff, Serge
%Y Terryn, Ayla Rigouts
%Y Zweigenbaum, Pierre
%Y Rapp, Reinhard
%S Proceedings of the 18th Workshop on Building and Using Comparable Corpora (BUCC)
%D 2025
%8 January
%I Association for Computational Linguistics
%C Abu Dhabi, UAE
%F meyers-etal-2025-role
%X Translating between languages with drastically different grammatical conventions poses significant challenges, not just for human interpreters but also for machine translation systems. In this work, we specifically target the translation challenges posed by attributive nouns in Chinese, which frequently cause ambiguities in English translation. By manually inserting the omitted particle ‘DE’ in news article titles from the Penn Chinese Discourse Treebank, we developed a targeted dataset to fine-tune Hugging Face Chinese to English translation models, specifically improving how this critical function word is handled. This focused approach not only complements the broader strategies suggested by previous studies but also offers a practical enhancement by specifically addressing a common error type in Chinese-English translation.
%U https://aclanthology.org/2025.bucc-1.7/
%P 57-61
Markdown (Informal)
[The Role of Handling Attributive Nouns in Improving Chinese-To-English Machine Translation](https://aclanthology.org/2025.bucc-1.7/) (Meyers et al., BUCC 2025)
ACL