A web-based unsupervised algorithm for learning transliteration model to improve translation of low-frequency proper names

Min Shiang Shia, Jiun Hung Lin, Scott Yu, Wen-Hsiang Lu

研究成果: Conference contribution

3 引文 斯高帕斯(Scopus)

摘要

In machine translation, cross-language information retrieval, and cross-language question answering, the problems of unknown term translation are difficult to be solved. Although we have proposed several effective Web-based term translation extraction methods exploring Web resources to deal with translation of frequent Web query terms. However, many low-frequency unknown terms are still difficult to be translated by using our previous Web-based term translation extraction methods. Therefore, in this paper we propose a two-stage hybrid translation extraction method, which is composed of our pervious Web-based term translation extraction method and a new Web-based transliteration method to improve translation of low-frequency unknown proper names. Additionally, to construct a good quality transliteration model, we also present a Web-based unsupervised learning algorithm to automatically collect diverse English-Chinese transliteration pairs from the Web. Experimental results showed that our new method can make great improvements for translation of unknown proper names.

原文English
主出版物標題Proceedings of 2005 IEEE International Conference on Natural Language Processing and Knowledge Engineering, IEEE NLP-KE'05
頁面420-425
頁數6
DOIs
出版狀態Published - 2005 十二月 1
事件2005 IEEE International Conference on Natural Language Processing and Knowledge Engineering, IEEE NLP-KE'05 - Wuhan, China
持續時間: 2005 十月 302005 十一月 1

出版系列

名字Proceedings of 2005 IEEE International Conference on Natural Language Processing and Knowledge Engineering, IEEE NLP-KE'05
2005

Other

Other2005 IEEE International Conference on Natural Language Processing and Knowledge Engineering, IEEE NLP-KE'05
國家/地區China
城市Wuhan
期間05-10-3005-11-01

All Science Journal Classification (ASJC) codes

  • 工程 (全部)

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