@inproceedings{gordon-passonneau-2010-evaluation,
title = "An Evaluation Framework for Natural Language Understanding in Spoken Dialogue Systems",
author = "Gordon, Joshua B. and
Passonneau, Rebecca J.",
editor = "Calzolari, Nicoletta and
Choukri, Khalid and
Maegaard, Bente and
Mariani, Joseph and
Odijk, Jan and
Piperidis, Stelios and
Rosner, Mike and
Tapias, Daniel",
booktitle = "Proceedings of the Seventh International Conference on Language Resources and Evaluation ({LREC}'10)",
month = may,
year = "2010",
address = "Valletta, Malta",
publisher = "European Language Resources Association (ELRA)",
url = "http://www.lrec-conf.org/proceedings/lrec2010/pdf/928_Paper.pdf",
abstract = "We present an evaluation framework to enable developers of information seeking, transaction based spoken dialogue systems to compare the robustness of natural language understanding (NLU) approaches across varying levels of word error rate and contrasting domains. We develop statistical and semantic parsing based approaches to dialogue act identification and concept retrieval. Voice search is used in each approach to ultimately query the database. Included in the framework is a method for developers to bootstrap a representative pseudo-corpus, which is used to estimate NLU performance in a new domain. We illustrate the relative merits of these NLU techniques by contrasting our statistical NLU approach with a semantic parsing method over two contrasting applications, our CheckItOut library system and the deployed Lets Go Public! system, across four levels of word error rate. We find that with respect to both dialogue act identification and concept retrieval, our statistical NLU approach is more likely to robustly accommodate the freer form, less constrained utterances of CheckItOut at higher word error rates than is possible with semantic parsing.",
}
<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="gordon-passonneau-2010-evaluation">
<titleInfo>
<title>An Evaluation Framework for Natural Language Understanding in Spoken Dialogue Systems</title>
</titleInfo>
<name type="personal">
<namePart type="given">Joshua</namePart>
<namePart type="given">B</namePart>
<namePart type="family">Gordon</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Rebecca</namePart>
<namePart type="given">J</namePart>
<namePart type="family">Passonneau</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2010-05</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC’10)</title>
</titleInfo>
<name type="personal">
<namePart type="given">Nicoletta</namePart>
<namePart type="family">Calzolari</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Khalid</namePart>
<namePart type="family">Choukri</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Bente</namePart>
<namePart type="family">Maegaard</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Joseph</namePart>
<namePart type="family">Mariani</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Jan</namePart>
<namePart type="family">Odijk</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Stelios</namePart>
<namePart type="family">Piperidis</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Mike</namePart>
<namePart type="family">Rosner</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Daniel</namePart>
<namePart type="family">Tapias</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<originInfo>
<publisher>European Language Resources Association (ELRA)</publisher>
<place>
<placeTerm type="text">Valletta, Malta</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
</relatedItem>
<abstract>We present an evaluation framework to enable developers of information seeking, transaction based spoken dialogue systems to compare the robustness of natural language understanding (NLU) approaches across varying levels of word error rate and contrasting domains. We develop statistical and semantic parsing based approaches to dialogue act identification and concept retrieval. Voice search is used in each approach to ultimately query the database. Included in the framework is a method for developers to bootstrap a representative pseudo-corpus, which is used to estimate NLU performance in a new domain. We illustrate the relative merits of these NLU techniques by contrasting our statistical NLU approach with a semantic parsing method over two contrasting applications, our CheckItOut library system and the deployed Lets Go Public! system, across four levels of word error rate. We find that with respect to both dialogue act identification and concept retrieval, our statistical NLU approach is more likely to robustly accommodate the freer form, less constrained utterances of CheckItOut at higher word error rates than is possible with semantic parsing.</abstract>
<identifier type="citekey">gordon-passonneau-2010-evaluation</identifier>
<location>
<url>http://www.lrec-conf.org/proceedings/lrec2010/pdf/928_Paper.pdf</url>
</location>
<part>
<date>2010-05</date>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T An Evaluation Framework for Natural Language Understanding in Spoken Dialogue Systems
%A Gordon, Joshua B.
%A Passonneau, Rebecca J.
%Y Calzolari, Nicoletta
%Y Choukri, Khalid
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Odijk, Jan
%Y Piperidis, Stelios
%Y Rosner, Mike
%Y Tapias, Daniel
%S Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC’10)
%D 2010
%8 May
%I European Language Resources Association (ELRA)
%C Valletta, Malta
%F gordon-passonneau-2010-evaluation
%X We present an evaluation framework to enable developers of information seeking, transaction based spoken dialogue systems to compare the robustness of natural language understanding (NLU) approaches across varying levels of word error rate and contrasting domains. We develop statistical and semantic parsing based approaches to dialogue act identification and concept retrieval. Voice search is used in each approach to ultimately query the database. Included in the framework is a method for developers to bootstrap a representative pseudo-corpus, which is used to estimate NLU performance in a new domain. We illustrate the relative merits of these NLU techniques by contrasting our statistical NLU approach with a semantic parsing method over two contrasting applications, our CheckItOut library system and the deployed Lets Go Public! system, across four levels of word error rate. We find that with respect to both dialogue act identification and concept retrieval, our statistical NLU approach is more likely to robustly accommodate the freer form, less constrained utterances of CheckItOut at higher word error rates than is possible with semantic parsing.
%U http://www.lrec-conf.org/proceedings/lrec2010/pdf/928_Paper.pdf
Markdown (Informal)
[An Evaluation Framework for Natural Language Understanding in Spoken Dialogue Systems](http://www.lrec-conf.org/proceedings/lrec2010/pdf/928_Paper.pdf) (Gordon & Passonneau, LREC 2010)
ACL