Paper: Local lexical adaptation in Machine Translation through triangulation: SMT helping SMT

ACL ID C10-1027
Title Local lexical adaptation in Machine Translation through triangulation: SMT helping SMT
Venue International Conference on Computational Linguistics
Session Main Conference
Year 2010
Authors

We present a framework where auxiliary MT systems are used to provide lexical predictions to a main SMT system. In this work, predictions are obtained by means of pivoting via auxiliary languages, and introduced into the main SMT sys- tem in the form of a low order language model, which is estimated on a sentence- by-sentence basis. The linear combination of models implemented by the decoder is thus extended with this additional lan- guage model. Experiments are carried out over three different translation tasks using the European Parliament corpus. For each task, nine additional languages are used as auxiliary languages to obtain the trian- gulated predictions. Translation accuracy results show that improvements in trans- lation quality are obtained, even for large data conditions.