Abstract
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.
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© 2006 Springer-Verlag Berlin Heidelberg
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Tantuğ, A.C., Adalı, E., Oflazer, K. (2006). Lexical Ambiguity Resolution for Turkish in Direct Transfer Machine Translation Models. In: Levi, A., Savaş, E., Yenigün, H., Balcısoy, S., Saygın, Y. (eds) Computer and Information Sciences – ISCIS 2006. ISCIS 2006. Lecture Notes in Computer Science, vol 4263. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11902140_26
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DOI: https://doi.org/10.1007/11902140_26
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-47242-1
Online ISBN: 978-3-540-47243-8
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