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Learning of Linear Ordering Problems and its Application to J-E Patent Translation in NTCIR-9 PatentMT.

, , , , , and . NTCIR, National Institute of Informatics (NII), (2011)

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Reliable utterance segment recognition by integrating a grammar with statistical language constraints., , , and . Speech Commun., 26 (4): 299-309 (1998)Post-ordering in Statistical Machine Translation., , , , and . MTSummit, (2011)English-Japanese Machine Translation for Lecture Subtitles using Back-Translation and Transfer Learning., , and . GCCE, page 728-730. IEEE, (2020)Spoken Interactive ODQA System: SPIQA., , , , , and . ACL (Companion), page 153-156. The Association for Computer Linguistics, (2003)A Comparative Study of Target Dependency Structures for Statistical Machine Translation., , , , and . ACL (2), page 100-104. The Association for Computer Linguistics, (2012)Efficient Decoding for Statistical Machine Translation with a Fully Expanded WFST Model., and . EMNLP, page 427-433. ACL, (2004)Improvement of word alignment models for Vietnamese-to-English translation., , and . IWSLT (Evaluation Campaign), (2015)A left-to-right processing model of pausing in Japanese based on limited syntactic information.. ICSLP, page 1353-1356. ISCA, (1996)Integration of grammar and statistical language constraints for partial word-sequence recognition., , and . EUROSPEECH, page 2759-2762. ISCA, (1997)N-Best Reranking by Multitask Learning., , , , and . WMT@ACL, page 375-383. Association for Computational Linguistics, (2010)