Abstract
This paper describes our approach to “NEWS 2009 Machine Transliteration Shared Task.” We built multiple transliteration engines based on different combinations of two transliteration models and three machine learning algorithms. Then, the outputs from these transliteration engines were combined using re-ranking functions. Our method was applied to all language pairs in “NEWS 2009 Machine Transliteration Shared Task.” The official results of our standard runs were ranked the best for four language pairs and the second best for three language pairs.
Cite
CITATION STYLE
Oh, J. H., Uchimoto, K., & Torisawa, K. (2009). Machine transliteration using target-language grapheme and phoneme: Multi-engine transliteration approach. In NEWS 2009 - 2009 Named Entities Workshop: Shared Task on Transliteration at the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP, ACL-IJCNLP 2009 (pp. 36–39). Association for Computational Linguistics (ACL).
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