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        <title>Learning Database Content for Spoken Dialogue System Design</title>
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    <name type="personal">
        <namePart type="given">Joseph</namePart>
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            <title>Proceedings of the Fifth International Conference on Language Resources and Evaluation (LREC’06)</title>
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        <name type="personal">
            <namePart type="given">Nicoletta</namePart>
            <namePart type="family">Calzolari</namePart>
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        <name type="personal">
            <namePart type="given">Khalid</namePart>
            <namePart type="family">Choukri</namePart>
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            <namePart type="given">Aldo</namePart>
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            <namePart type="given">Joseph</namePart>
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            <namePart type="given">Jan</namePart>
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        <name type="personal">
            <namePart type="given">Daniel</namePart>
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    <abstract>Spoken dialogue systems are common interfaces to backend data in information retrieval domains. As more data is made available on the Web and IE technology matures, dialogue systems, whether they be speech- or text-based, will be more in demand to provide user-friendly access to this data. However, dialogue systems must become both easier to configure, as well as more informative than the traditional form-based systems that are currently available. We present techniques in this paper to address the issue of automating both content selection for use in summary responses and in system initiative queries.</abstract>
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%0 Conference Proceedings
%T Learning Database Content for Spoken Dialogue System Design
%A Polifroni, Joseph
%A Walker, Marilyn
%Y Calzolari, Nicoletta
%Y Choukri, Khalid
%Y Gangemi, Aldo
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Odijk, Jan
%Y Tapias, Daniel
%S Proceedings of the Fifth International Conference on Language Resources and Evaluation (LREC’06)
%D 2006
%8 May
%I European Language Resources Association (ELRA)
%C Genoa, Italy
%F polifroni-walker-2006-learning
%X Spoken dialogue systems are common interfaces to backend data in information retrieval domains. As more data is made available on the Web and IE technology matures, dialogue systems, whether they be speech- or text-based, will be more in demand to provide user-friendly access to this data. However, dialogue systems must become both easier to configure, as well as more informative than the traditional form-based systems that are currently available. We present techniques in this paper to address the issue of automating both content selection for use in summary responses and in system initiative queries.
%U http://www.lrec-conf.org/proceedings/lrec2006/pdf/301_pdf.pdf

Markdown (Informal)

[Learning Database Content for Spoken Dialogue System Design](http://www.lrec-conf.org/proceedings/lrec2006/pdf/301_pdf.pdf) (Polifroni & Walker, LREC 2006)

• Learning Database Content for Spoken Dialogue System Design (Polifroni & Walker, LREC 2006)

ACL

• Joseph Polifroni and Marilyn Walker. 2006. Learning Database Content for Spoken Dialogue System Design. In Proceedings of the Fifth International Conference on Language Resources and Evaluation (LREC’06), Genoa, Italy. European Language Resources Association (ELRA).