@inproceedings{kazi-etal-2013-mit,
title = "The {MIT}-{LL}/{AFRL} {IWSLT}-2013 {MT} system",
author = "Kazi, Michaeel and
Coury, Michael and
Salesky, Elizabeth and
Ray, Jessica and
Shen, Wade and
Gleason, Terry and
Anderson, Tim and
Erdmann, Grant and
Schwartz, Lane and
Ore, Brian and
Slyh, Raymond and
Gwinnup, Jeremy and
Young, Katherine and
Hutt, Michael",
editor = "Zhang, Joy Ying",
booktitle = "Proceedings of the 10th International Workshop on Spoken Language Translation: Evaluation Campaign",
month = dec # " 5-6",
year = "2013",
address = "Heidelberg, Germany",
url = "https://aclanthology.org/2013.iwslt-evaluation.17",
abstract = "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.",
}
<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="kazi-etal-2013-mit">
<titleInfo>
<title>The MIT-LL/AFRL IWSLT-2013 MT system</title>
</titleInfo>
<name type="personal">
<namePart type="given">Michaeel</namePart>
<namePart type="family">Kazi</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Michael</namePart>
<namePart type="family">Coury</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Elizabeth</namePart>
<namePart type="family">Salesky</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Jessica</namePart>
<namePart type="family">Ray</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Wade</namePart>
<namePart type="family">Shen</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Terry</namePart>
<namePart type="family">Gleason</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Tim</namePart>
<namePart type="family">Anderson</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Grant</namePart>
<namePart type="family">Erdmann</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Lane</namePart>
<namePart type="family">Schwartz</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Brian</namePart>
<namePart type="family">Ore</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Raymond</namePart>
<namePart type="family">Slyh</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Jeremy</namePart>
<namePart type="family">Gwinnup</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Katherine</namePart>
<namePart type="family">Young</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Michael</namePart>
<namePart type="family">Hutt</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2013-dec 5-6</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of the 10th International Workshop on Spoken Language Translation: Evaluation Campaign</title>
</titleInfo>
<name type="personal">
<namePart type="given">Joy</namePart>
<namePart type="given">Ying</namePart>
<namePart type="family">Zhang</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<originInfo>
<place>
<placeTerm type="text">Heidelberg, Germany</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
</relatedItem>
<abstract>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.</abstract>
<identifier type="citekey">kazi-etal-2013-mit</identifier>
<location>
<url>https://aclanthology.org/2013.iwslt-evaluation.17</url>
</location>
<part>
<date>2013-dec 5-6</date>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T The MIT-LL/AFRL IWSLT-2013 MT system
%A Kazi, Michaeel
%A Coury, Michael
%A Salesky, Elizabeth
%A Ray, Jessica
%A Shen, Wade
%A Gleason, Terry
%A Anderson, Tim
%A Erdmann, Grant
%A Schwartz, Lane
%A Ore, Brian
%A Slyh, Raymond
%A Gwinnup, Jeremy
%A Young, Katherine
%A Hutt, Michael
%Y Zhang, Joy Ying
%S Proceedings of the 10th International Workshop on Spoken Language Translation: Evaluation Campaign
%D 2013
%8 dec 5 6
%C Heidelberg, Germany
%F kazi-etal-2013-mit
%X 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.
%U https://aclanthology.org/2013.iwslt-evaluation.17
Markdown (Informal)
[The MIT-LL/AFRL IWSLT-2013 MT system](https://aclanthology.org/2013.iwslt-evaluation.17) (Kazi et al., IWSLT 2013)
ACL
- 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, and Michael Hutt. 2013. The MIT-LL/AFRL IWSLT-2013 MT system. In Proceedings of the 10th International Workshop on Spoken Language Translation: Evaluation Campaign, Heidelberg, Germany.