This paper presents a statistical lexical ambiguity resolution method in direct transfer machine translation models in which the target language is Turkish. Since direct transfer MT models do not have full syntactic information, most of the lexical ambiguity resolution methods are not very helpful. Our disambiguation model is based on statistical language models. We have investigated the performances of some statistical language model types and parameters in lexical ambiguity resolution for our direct transfer MT system. © Springer-Verlag Berlin Heidelberg 2006.
CITATION STYLE
Tantuǧ, A. C., Adali, E., & Oflazer, K. (2006). Lexical ambiguity resolution for Turkish in direct transfer machine translation models. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4263 LNCS, pp. 230–238). Springer Verlag. https://doi.org/10.1007/11902140_26
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