@inproceedings{sanders-etal-2008-odds,
title = "Odds of Successful Transfer of Low-Level Concepts: a Key Metric for Bidirectional Speech-to-Speech Machine Translation in {DARPA}{'}s {TRANSTAC} Program",
author = "Sanders, Gregory and
Bronsart, S{\'e}bastien and
Condon, Sherri and
Schlenoff, Craig",
editor = "Calzolari, Nicoletta and
Choukri, Khalid and
Maegaard, Bente and
Mariani, Joseph and
Odijk, Jan and
Piperidis, Stelios and
Tapias, Daniel",
booktitle = "Proceedings of the Sixth International Conference on Language Resources and Evaluation ({LREC}'08)",
month = may,
year = "2008",
address = "Marrakech, Morocco",
publisher = "European Language Resources Association (ELRA)",
url = "http://www.lrec-conf.org/proceedings/lrec2008/pdf/399_paper.pdf",
abstract = "The Spoken Language Communication and Translation System for Tactical Use (TRANSTAC) program is a Defense Advanced Research Agency (DARPA) program to create bidirectional speech-to-speech machine translation (MT) that will allow U.S. Soldiers and Marines, speaking only English, to communicate, in tactical situations, with civilian populations who speak only other languages (for example, Iraqi Arabic). A key metric for the program is the odds of successfully transferring low-level concepts, defined as the source-language content words. The National Institute of Standards and Technology (NIST) has now carried out two large-scale evaluations of TRANSTAC systems, using that metric. In this paper we discuss the merits of that metric. It has proven to be quite informative. We describe exactly how we defined this metric and how we obtained values for it from panels of bilingual judges allowing others to do what we have done. We compare results on this metric to results on Likert-type judgments of semantic adequacy, from the same panels of bilingual judges, as well as to a suite of typical automated MT metrics (BLEU, TER, METEOR).",
}
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<abstract>The Spoken Language Communication and Translation System for Tactical Use (TRANSTAC) program is a Defense Advanced Research Agency (DARPA) program to create bidirectional speech-to-speech machine translation (MT) that will allow U.S. Soldiers and Marines, speaking only English, to communicate, in tactical situations, with civilian populations who speak only other languages (for example, Iraqi Arabic). A key metric for the program is the odds of successfully transferring low-level concepts, defined as the source-language content words. The National Institute of Standards and Technology (NIST) has now carried out two large-scale evaluations of TRANSTAC systems, using that metric. In this paper we discuss the merits of that metric. It has proven to be quite informative. We describe exactly how we defined this metric and how we obtained values for it from panels of bilingual judges allowing others to do what we have done. We compare results on this metric to results on Likert-type judgments of semantic adequacy, from the same panels of bilingual judges, as well as to a suite of typical automated MT metrics (BLEU, TER, METEOR).</abstract>
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%0 Conference Proceedings
%T Odds of Successful Transfer of Low-Level Concepts: a Key Metric for Bidirectional Speech-to-Speech Machine Translation in DARPA’s TRANSTAC Program
%A Sanders, Gregory
%A Bronsart, Sébastien
%A Condon, Sherri
%A Schlenoff, Craig
%Y Calzolari, Nicoletta
%Y Choukri, Khalid
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Odijk, Jan
%Y Piperidis, Stelios
%Y Tapias, Daniel
%S Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC’08)
%D 2008
%8 May
%I European Language Resources Association (ELRA)
%C Marrakech, Morocco
%F sanders-etal-2008-odds
%X The Spoken Language Communication and Translation System for Tactical Use (TRANSTAC) program is a Defense Advanced Research Agency (DARPA) program to create bidirectional speech-to-speech machine translation (MT) that will allow U.S. Soldiers and Marines, speaking only English, to communicate, in tactical situations, with civilian populations who speak only other languages (for example, Iraqi Arabic). A key metric for the program is the odds of successfully transferring low-level concepts, defined as the source-language content words. The National Institute of Standards and Technology (NIST) has now carried out two large-scale evaluations of TRANSTAC systems, using that metric. In this paper we discuss the merits of that metric. It has proven to be quite informative. We describe exactly how we defined this metric and how we obtained values for it from panels of bilingual judges allowing others to do what we have done. We compare results on this metric to results on Likert-type judgments of semantic adequacy, from the same panels of bilingual judges, as well as to a suite of typical automated MT metrics (BLEU, TER, METEOR).
%U http://www.lrec-conf.org/proceedings/lrec2008/pdf/399_paper.pdf
Markdown (Informal)
[Odds of Successful Transfer of Low-Level Concepts: a Key Metric for Bidirectional Speech-to-Speech Machine Translation in DARPA’s TRANSTAC Program](http://www.lrec-conf.org/proceedings/lrec2008/pdf/399_paper.pdf) (Sanders et al., LREC 2008)
ACL