A statistical approach to machine translation
Computational Linguistics
A Maximum-Entropy-Inspired Parser
A Maximum-Entropy-Inspired Parser
Building a large annotated corpus of English: the penn treebank
Computational Linguistics - Special issue on using large corpora: II
Translation by structural correspondences
EACL '89 Proceedings of the fourth conference on European chapter of the Association for Computational Linguistics
Statistical parsing with a context-free grammar and word statistics
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
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English-Thai MT systems are nowadays restricted by incomplete vocabularies and translation knowledge. Users must consequently accept only one translation result that is sometimes semantically divergent or ungrammatical. With the according reason, we propose novel Internet-based translation assistant software in order to facilitate document translation from English to Thai. In this project, we utilize the structural transfer model as the mechanism. This project differs from current English-Thai MT systems in the aspects that it empowers the users to manually select the most appropriate translation from every possibility and to manually train new translation rules to the system if it is necessary. With the applied model, we over-come four translation problems---lexicon rear-rangement, structural ambiguity, phrase translation, and classifier generation. Finally, we started the system evaluation with 322 randomly selected sentences on the Future Magazine bilingual corpus and the system yielded 59.87% and 83.08% translation accuracy for the best case and the worse case based on 90.1% average precision of the parser.