This paper describes the statistical machine translation system developed at ITC-irst for the evaluation campaign of the International Workshop on Spoken Language Translation 2005. The system exploits two search passes: the first pass is performed by a beam-search decoder which generates an n-best list of translations, the second by a simple re-scoring algorithm. The two passes apply log-linear phrase-based models with an increasing number of feature functions. Runs have been submitted under the supplieddata and manual-transcription conditions for three language pairs: Chinese-to-English, Japanese-to-English and Arabicto- English. Moreover, the Japanese-to-English system has been also employed under the ASR first-best condition. Significant improvements are reported by exploiting alternative word-alignments, and by using novel feature functions in the re-scoring step.
Cite as: Chen, B., Cattoni, R., Bertoldi, N., Cettolo, M., Federico, M. (2005) The ITC-irst SMT system for IWSLT-2005. Proc. International Workshop on Spoken Language Translation (IWSLT 2005), 88-94
@inproceedings{chen05_iwslt,
author={Boxing Chen and Roldano Cattoni and Nicola Bertoldi and Mauro Cettolo and Marcello Federico},
title={{The ITC-irst SMT system for IWSLT-2005}},
year=2005,
booktitle={Proc. International Workshop on Spoken Language Translation (IWSLT 2005)},
pages={88--94}
}