A systematic comparison of various statistical alignment models
Computational Linguistics
Human-computer interaction for semantic disambiguation
COLING '90 Proceedings of the 13th conference on Computational linguistics - Volume 3
BLEU: a method for automatic evaluation of machine translation
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Statistical phrase-based translation
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
TransType: text prediction for translators
HLT '02 Proceedings of the second international conference on Human Language Technology Research
Statistical approaches to computer-assisted translation
Computational Linguistics
A web-based interactive computer aided translation tool
ACLDemos '09 Proceedings of the ACL-IJCNLP 2009 Software Demonstrations
Search right and thou shalt find...: using web queries for learner error detection
IUNLPBEA '10 Proceedings of the NAACL HLT 2010 Fifth Workshop on Innovative Use of NLP for Building Educational Applications
EdIt: a broad-coverage grammar checker using pattern grammar
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: Systems Demonstrations
An interactive machine translation system with online learning
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: Systems Demonstrations
GRASP: grammar- and syntax-based pattern-finder in CALL
IUNLPBEA '11 Proceedings of the 6th Workshop on Innovative Use of NLP for Building Educational Applications
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We introduce a method for learning to predict the following grammar and text of the ongoing translation given a source text. In our approach, predictions are offered aimed at reducing users' burden on lexical and grammar choices, and improving productivity. The method involves learning syntactic phraseology and translation equivalents. At run-time, the source and its translation prefix are sliced into ngrams to generate subsequent grammar and translation predictions. We present a prototype writing assistant, TransAhead, that applies the method to where computer-assisted translation and language learning meet. The preliminary results show that the method has great potentials in CAT and CALL (significant boost in translation quality is observed).