Automatic dialog acts recognition based on sentence structure
Identifieur interne : 005802 ( Main/Exploration ); précédent : 005801; suivant : 005803Automatic dialog acts recognition based on sentence structure
Auteurs : Pavel Kral [France] ; Christophe Cerisara [France] ; Jana Kleckova [République tchèque]Source :
English descriptors
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Abstract
This paper deals with automatic dialog acts (DAs) recognition in Czech. Our work focuses on two applications: a multimodal reservation system and an animated talking head for hearing-impaired people. In that context, we consider the following DAs: statements, orders, investigation questions and other questions. The main goal of this paper is to propose, implement and evaluate new approaches to automatic DAs recognition based on sentence structure and prosody. Our system is tested on a Czech corpus that simulates a task of train tickets reservation. With lexical-only information, the classification accuracy is 91 %. We proposed two methods to include sentence structure information, which respectively give 94 % and 95 %. When prosodic information is further considered, the recognition accuracy reaches 96 %.
Url:
Affiliations:
- France, République tchèque
- Grand Est, Lorraine (région)
- Nancy
- Institut national polytechnique de Lorraine, Université Nancy 2, Université de Lorraine
Links toward previous steps (curation, corpus...)
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Le document en format XML
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<orgName type="university">Université Nancy 2</orgName>
<orgName type="institution" wicri:auto="newGroup">Université de Lorraine</orgName>
<placeName><settlement type="city">Nancy</settlement>
<region type="region" nuts="2">Grand Est</region>
<region type="old region" nuts="2">Lorraine (région)</region>
</placeName>
<orgName type="university">Institut national polytechnique de Lorraine</orgName>
<orgName type="institution" wicri:auto="newGroup">Université de Lorraine</orgName>
</affiliation>
</author>
<author><name sortKey="Kleckova, Jana" sort="Kleckova, Jana" uniqKey="Kleckova J" first="Jana" last="Kleckova">Jana Kleckova</name>
<affiliation wicri:level="1"><hal:affiliation type="laboratory" xml:id="struct-14773" status="INCOMING"><orgName>Département de l'informatique</orgName>
<orgName type="acronym">ZCU-FAV</orgName>
<desc><address><country key="CZ"></country>
</address>
</desc>
<listRelation><relation active="#struct-306098" type="direct"></relation>
</listRelation>
<tutelles><tutelle active="#struct-306098" type="direct"><org type="institution" xml:id="struct-306098" status="INCOMING"><orgName>Université de Bohème de l'Ouest</orgName>
<desc><address><country key="FR"></country>
</address>
</desc>
</org>
</tutelle>
</tutelles>
</hal:affiliation>
<country>République tchèque</country>
</affiliation>
</author>
</analytic>
</biblStruct>
</sourceDesc>
</fileDesc>
<profileDesc><textClass><keywords scheme="mix" xml:lang="en"><term>bayesian network</term>
<term>dialog act</term>
<term>language model</term>
<term>prosody</term>
</keywords>
</textClass>
</profileDesc>
</teiHeader>
<front><div type="abstract" xml:lang="en">This paper deals with automatic dialog acts (DAs) recognition in Czech. Our work focuses on two applications: a multimodal reservation system and an animated talking head for hearing-impaired people. In that context, we consider the following DAs: statements, orders, investigation questions and other questions. The main goal of this paper is to propose, implement and evaluate new approaches to automatic DAs recognition based on sentence structure and prosody. Our system is tested on a Czech corpus that simulates a task of train tickets reservation. With lexical-only information, the classification accuracy is 91 %. We proposed two methods to include sentence structure information, which respectively give 94 % and 95 %. When prosodic information is further considered, the recognition accuracy reaches 96 %.</div>
</front>
</TEI>
<affiliations><list><country><li>France</li>
<li>République tchèque</li>
</country>
<region><li>Grand Est</li>
<li>Lorraine (région)</li>
</region>
<settlement><li>Nancy</li>
</settlement>
<orgName><li>Institut national polytechnique de Lorraine</li>
<li>Université Nancy 2</li>
<li>Université de Lorraine</li>
</orgName>
</list>
<tree><country name="France"><region name="Grand Est"><name sortKey="Kral, Pavel" sort="Kral, Pavel" uniqKey="Kral P" first="Pavel" last="Kral">Pavel Kral</name>
</region>
<name sortKey="Cerisara, Christophe" sort="Cerisara, Christophe" uniqKey="Cerisara C" first="Christophe" last="Cerisara">Christophe Cerisara</name>
</country>
<country name="République tchèque"><noRegion><name sortKey="Kleckova, Jana" sort="Kleckova, Jana" uniqKey="Kleckova J" first="Jana" last="Kleckova">Jana Kleckova</name>
</noRegion>
</country>
</tree>
</affiliations>
</record>
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