Lexical ambiguity resolution for Turkish in direct transfer machine translation models

A. Cüneyd Tantuǧ*, Eşref Adali, Kemal Oflazer

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

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.

Original languageEnglish
Title of host publicationComputer and Information Sciences - ISCIS 2006
Subtitle of host publication21th International Symposium, Proceedings
PublisherSpringer Verlag
Pages230-238
Number of pages9
ISBN (Print)3540472428, 9783540472421
Publication statusPublished - 2006
EventISCIS 2006: 21th International Symposium on Computer and Information Sciences - Istanbul, Turkey
Duration: 1 Nov 20063 Nov 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4263 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceISCIS 2006: 21th International Symposium on Computer and Information Sciences
Country/TerritoryTurkey
CityIstanbul
Period1/11/063/11/06

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