Most statistical machine translation systems employ a word-based alignment model. In this paper we demonstrate that word-based alignment is a major cause of translation errors. We...
This paper describes a novel method by which a dialogue agent can learn to choose an optimal dialogue strategy. While it is widely agreed that dialogue strategies should be formul...
Marilyn A. Walker, Jeanne Frommer, Shrikanth Naray...
We describe an on-going project whose primary aim is to establish the technology of producing closed captions for TV news programs efficiently using natural language processing an...
In this paper, we address the issue of syntagmatic expressions from a computational lexical semantic perspective. From a representational viewpoint, we argue for a hybrid approach...
This paper proposes a novel method for learning probability models of subcategorization preference of verbs. We consider the issues of case dependencies and noun class generalizat...
A method is presented for automatically augmenting the bilingual lexicon of an existing Machine Translation system, by extracting bilingual entries from aligned bilingual text. Th...
This paper examines the feasibility of using statistical methods to train a part-of-speech predictor for unknown words. By using statistical methods, without incorporating hand-cr...