Article details

Research area
Natural language & AI

International Workshop on Spoken Language Translation, Trento, Italy


Wade Shen, Tim Anderson, Ray Slyh

The MIT-LL/AFRL IWSLT-2007 MT System


The MIT-LL/AFRL MT system implements a standard phrase-based, statistical translation model. It incorporates a number of extensions that improve performance for speech-based translation. During this evaluation our efforts focused on the rapid porting of our SMT system to a new language (Arabic) and novel approaches to translation from speech in­put.

This paper discusses the architecture of the MIT-LL/AFRL MT system, improvements over our 2007 system, and experiments we ran during the IWSLT-2007 evaluation. Specifically, we focus on 1) experiments comparing the per­formance of confusion network decoding and direct lattice decoding techniques for speech machine translation, 2) the application of lightweight morphology for Arabic MT pre­processing and 3) improved confusion network decoding.

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