Nguyen Bach

Cohesive Constraints in A Beam Search Phrase-based Decoder

Cohesive constraints allow the phrase-based decoder to employ arbitrary, non-syntactic phrases, and encourage it to translate those phrases in an order that respects the source dependency tree structure. We present extensions of the cohesive constraints, such as exhaustive interruption count and rich interruption check. We show that the cohesion-enhanced decoder significantly outperforms the standard phrase-based decoder on English→Spanish. Improvements between 0.5 and 1.2 BLEU point are obtained on English→Iraqi system.

Incremental Adaptation of Speech-to-Speech Translation

In building practical two-way speech-to-speech translation systems the end user will always wish to use the system in an environment different from the original training data. As with all speech systems, it is important to allow the system to adapt to the actual usage situations. This paper investigates how a speech-to-speech translation system can adapt day-to-day from collected data on day one to improve performance on day two. The platform is the CMU Iraqi-English portable two-way speech-to-speech system as developed under the DARPA TransTac program. We show how machine translation, speech recognition and overall system performance can be improved on day 2 after adapting from day 1 in both a supervised and unsupervised way.

Improving Word Alignment with Language Model Based Confidence Scores

This paper describes the statistical machine translation systems submitted to the ACL-WMT 2008 shared translation task. Systems were submitted for two translation directions: English→Spanish and Spanish→English. Using sentence pair confidence scores estimated with source and target language models, improvements are observed on the News-Commentary test sets. Genre-dependent sentence pair confidence score and integration of sentence pair confidence score into phrase table are also investigated.

Recent Improvements in the CMU Large Scale Chinese-English SMT System

In this paper we describe recent improvements to components and methods used in our statistical machine translation system for Chinese-English used in the January 2008 GALE evaluation. Main improvements are results of consistent data processing, larger statistical models and a POS-based word reordering approach.