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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence, 35 / No. 16: AAAI-21 Technical Tracks 16

Bridging the Domain Gap: Improve Informal Language Translation via Counterfactual Domain Adaptation

February 1, 2023

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Authors

Ke Wang

Peking University


Guandan Chen

Alibaba Group


Zhongqiang Huang

Alibaba Group


Xiaojun Wan

Peking University


Fei Huang

Alibaba Group


DOI:

10.1609/aaai.v35i16.17645


Abstract:

Despite the near-human performances already achieved on formal texts such as news articles, neural machine translation still has difficulty in dealing with "user-generated" texts that have diverse linguistic phenomena but lack large-scale high-quality parallel corpora. To address this problem, we propose a counterfactual domain adaptation method to better leverage both large-scale source-domain data (formal texts) and small-scale target-domain data (informal texts). Specifically, by considering effective counterfactual conditions (the concatenations of source-domain texts and the target-domain tag), we construct the counterfactual representations to fill the sparse latent space of the target domain caused by a small amount of data, that is, bridging the gap between the source-domain data and the target-domain data. Experiments on English-to-Chinese and Chinese-to-English translation tasks show that our method outperforms the base model that is trained only on the informal corpus by a large margin, and consistently surpasses different baseline methods by +1.12 ~ 4.34 BLEU points on different datasets. Furthermore, we also show that our method achieves competitive performances on cross-domain language translation on four language pairs.

Topics: AAAI

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HOW TO CITE:

Ke Wang||Guandan Chen||Zhongqiang Huang||Xiaojun Wan||Fei Huang Bridging the Domain Gap: Improve Informal Language Translation via Counterfactual Domain Adaptation Proceedings of the AAAI Conference on Artificial Intelligence (2021) 13970-13978.

Ke Wang||Guandan Chen||Zhongqiang Huang||Xiaojun Wan||Fei Huang Bridging the Domain Gap: Improve Informal Language Translation via Counterfactual Domain Adaptation AAAI 2021, 13970-13978.

Ke Wang||Guandan Chen||Zhongqiang Huang||Xiaojun Wan||Fei Huang (2021). Bridging the Domain Gap: Improve Informal Language Translation via Counterfactual Domain Adaptation. Proceedings of the AAAI Conference on Artificial Intelligence, 13970-13978.

Ke Wang||Guandan Chen||Zhongqiang Huang||Xiaojun Wan||Fei Huang. Bridging the Domain Gap: Improve Informal Language Translation via Counterfactual Domain Adaptation. Proceedings of the AAAI Conference on Artificial Intelligence 2021 p.13970-13978.

Ke Wang||Guandan Chen||Zhongqiang Huang||Xiaojun Wan||Fei Huang. 2021. Bridging the Domain Gap: Improve Informal Language Translation via Counterfactual Domain Adaptation. "Proceedings of the AAAI Conference on Artificial Intelligence". 13970-13978.

Ke Wang||Guandan Chen||Zhongqiang Huang||Xiaojun Wan||Fei Huang. (2021) "Bridging the Domain Gap: Improve Informal Language Translation via Counterfactual Domain Adaptation", Proceedings of the AAAI Conference on Artificial Intelligence, p.13970-13978

Ke Wang||Guandan Chen||Zhongqiang Huang||Xiaojun Wan||Fei Huang, "Bridging the Domain Gap: Improve Informal Language Translation via Counterfactual Domain Adaptation", AAAI, p.13970-13978, 2021.

Ke Wang||Guandan Chen||Zhongqiang Huang||Xiaojun Wan||Fei Huang. "Bridging the Domain Gap: Improve Informal Language Translation via Counterfactual Domain Adaptation". Proceedings of the AAAI Conference on Artificial Intelligence, 2021, p.13970-13978.

Ke Wang||Guandan Chen||Zhongqiang Huang||Xiaojun Wan||Fei Huang. "Bridging the Domain Gap: Improve Informal Language Translation via Counterfactual Domain Adaptation". Proceedings of the AAAI Conference on Artificial Intelligence, (2021): 13970-13978.

Ke Wang||Guandan Chen||Zhongqiang Huang||Xiaojun Wan||Fei Huang. Bridging the Domain Gap: Improve Informal Language Translation via Counterfactual Domain Adaptation. AAAI[Internet]. 2021[cited 2023]; 13970-13978.


ISSN: 2374-3468


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