Abstract
This paper describes DFKI's participation in the NEWS2011 shared task on machine transliteration. Our primary system participated in the evaluation for English-Chinese and Chinese-English language pairs. We extended the joint source-channel model on the transliteration task into a multi-to-multi joint source-channel model, which allows alignments between substrings of arbitrary lengths in both source and target strings. When the model is integrated into a modified phrase-based statistical machine translation system, around 20% of improvement is observed. The primary system achieved 0.320 on English-Chinese and 0.133 on Chinese-English in terms of top-1 accuracy.
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Chen, Y., Wang, R., & Zhang, Y. (2011). Statistical Machine Transliteration with Multi-to-Multi Joint Source Channel Model. Proceedings of the Named Entities Workshop Shared Task on Machine Transliteration. The IJCNLP Named Entities Workshop Shared Task on Machine Transliteration (NEWS-2011), Located at International Joint Conference on Natural Language Processing, November 12, 101–105. Retrieved from http://www.dfki.de/web/forschung/publikationen/renameFileForDownload?filename=NEWS2011.pdf&file_id=uploads_1127
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