@inproceedings{5ea85beabca2482f9936c13f7b560beb,
title = "Improve statistical machine translation with context-sensitive bilingual semantic embedding model",
abstract = "We investigate how to improve bilingual embedding which has been successfully used as a feature in phrase-based statistical machine translation (SMT). Despite bilingual embedding's success, the contextual information, which is of critical importance to translation quality, was ignored in previous work. To employ the contextual information, we propose a simple and memory-efficient model for learning bilingual embedding, taking both the source phrase and context around the phrase into account. Bilingual translation scores generated from our proposed bilingual embedding model are used as features in our SMT system. Experimental results show that the proposed method achieves significant improvements on large-scale Chinese-English translation task.",
author = "Haiyang Wu and Daxiang Dong and Wei He and Xiaoguang Hu and Dianhai Yu and Hua Wu and Haifeng Wang and Ting Liu",
note = "Publisher Copyright: {\textcopyright} 2014 Association for Computational Linguistics.; 2014 Conference on Empirical Methods in Natural Language Processing, EMNLP 2014 ; Conference date: 25-10-2014 Through 29-10-2014",
year = "2014",
doi = "10.3115/v1/d14-1015",
language = "英语",
series = "EMNLP 2014 - 2014 Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference",
publisher = "Association for Computational Linguistics (ACL)",
pages = "142--146",
booktitle = "EMNLP 2014 - 2014 Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference",
address = "澳大利亚",
}