The MIT-LL/AFRL IWSLT-2008 MT System

This paper describes the MIT-LL/AFRL statistical MT system and the improvements that were developed during the IWSLT 2008 evaluation campaign. As part of these efforts, we experimented with a number of extensions to the standard phrase-based model that improve performance for both text and speech-based translation on Chinese and Arabic translation tasks. We discuss the architecture of the MIT-LL/AFRL MT system, improvements over our 2007 system, and experiments we ran during the IWSLT-2008 evaluation. Specifically, we focus on 1) novel segmentation models for phrasebased MT, 2) improved lattice and confusion network decoding of speech input, 3) improved Arabic morphology for MT preprocessing, and 4) system combination methods for machine translation.