Terry Gleason


2013

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The MIT-LL/AFRL IWSLT-2013 MT system
Michaeel Kazi | Michael Coury | Elizabeth Salesky | Jessica Ray | Wade Shen | Terry Gleason | Tim Anderson | Grant Erdmann | Lane Schwartz | Brian Ore | Raymond Slyh | Jeremy Gwinnup | Katherine Young | Michael Hutt
Proceedings of the 10th International Workshop on Spoken Language Translation: Evaluation Campaign

This paper describes the MIT-LL/AFRL statistical MT system and the improvements that were developed during the IWSLT 2013 evaluation campaign [1]. As part of these efforts, we experimented with a number of extensions to the standard phrase-based model that improve performance on the Russian to English, Chinese to English, Arabic to English, and English to French TED-talk translation task. We also applied our existing ASR system to the TED-talk lecture ASR task. We discuss the architecture of the MIT-LL/AFRL MT system, improvements over our 2012 system, and experiments we ran during the IWSLT-2013 evaluation. Specifically, we focus on 1) cross-entropy filtering of MT training data, and 2) improved optimization techniques, 3) language modeling, and 4) approximation of out-of-vocabulary words.

2012

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The MIT-LL/AFRL IWSLT 2012 MT system
Jennifer Drexler | Wade Shen | Tim Anderson | Raymond Slyh | Brian Ore | Eric Hansen | Terry Gleason
Proceedings of the 9th International Workshop on Spoken Language Translation: Evaluation Campaign

This paper describes the MIT-LL/AFRL statistical MT system and the improvements that were developed during the IWSLT 2012 evaluation campaign. As part of these efforts, we experimented with a number of extensions to the standard phrase-based model that improve performance on the Arabic to English and English to French TED-talk translation task. We also applied our existing ASR system to the TED-talk lecture ASR task, and combined our ASR and MT systems for the TED-talk SLT task. We discuss the architecture of the MIT-LL/AFRL MT system, improvements over our 2011 system, and experiments we ran during the IWSLT-2012 evaluation. Specifically, we focus on 1) cross-domain translation using MAP adaptation, 2) cross-entropy filtering of MT training data, and 3) improved Arabic morphology for MT preprocessing.

2011

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The MIT-LL/AFRL IWSLT-2011 MT system
A. Ryan Aminzadeh | Tim Anderson | Ray Slyh | Brian Ore | Eric Hansen | Wade Shen | Jennifer Drexler | Terry Gleason
Proceedings of the 8th International Workshop on Spoken Language Translation: Evaluation Campaign

This paper describes the MIT-LL/AFRL statistical MT system and the improvements that were developed during the IWSLT 2011 evaluation campaign. As part of these efforts, we experimented with a number of extensions to the standard phrase-based model that improve performance on the Arabic to English and English to French TED-talk translation tasks. We also applied our existing ASR system to the TED-talk lecture ASR task. We discuss the architecture of the MIT-LL/AFRL MT system, improvements over our 2010 system, and experiments we ran during the IWSLT-2011 evaluation. Specifically, we focus on 1) speech recognition for lecture-like data, 2) cross-domain translation using MAP adaptation, and 3) improved Arabic morphology for MT preprocessing.