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        <title>Combining Multiple Models for Speech Information Retrieval</title>
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    <name type="personal">
        <namePart type="given">Muath</namePart>
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        <namePart type="given">Diana</namePart>
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            <title>Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC’08)</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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        <name type="personal">
            <namePart type="given">Bente</namePart>
            <namePart type="family">Maegaard</namePart>
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            <namePart type="given">Joseph</namePart>
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        <name type="personal">
            <namePart type="given">Jan</namePart>
            <namePart type="family">Odijk</namePart>
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        <name type="personal">
            <namePart type="given">Stelios</namePart>
            <namePart type="family">Piperidis</namePart>
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        <name type="personal">
            <namePart type="given">Daniel</namePart>
            <namePart type="family">Tapias</namePart>
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    <abstract>In this article we present a method for combining different information retrieval models in order to increase the retrieval performance in a Speech Information Retrieval task. The formulas for combining the models are tuned on training data. Then the system is evaluated on test data. The task is particularly difficult because the text collection is automatically transcribed spontaneous speech, with many recognition errors. Also, the topics are real information needs, difficult to satisfy. Information Retrieval systems are not able to obtain good results on this data set, except for the case when manual summaries are included.</abstract>
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%0 Conference Proceedings
%T Combining Multiple Models for Speech Information Retrieval
%A Alzghool, Muath
%A Inkpen, Diana
%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 alzghool-inkpen-2008-combining
%X In this article we present a method for combining different information retrieval models in order to increase the retrieval performance in a Speech Information Retrieval task. The formulas for combining the models are tuned on training data. Then the system is evaluated on test data. The task is particularly difficult because the text collection is automatically transcribed spontaneous speech, with many recognition errors. Also, the topics are real information needs, difficult to satisfy. Information Retrieval systems are not able to obtain good results on this data set, except for the case when manual summaries are included.
%U http://www.lrec-conf.org/proceedings/lrec2008/pdf/45_paper.pdf

Markdown (Informal)

[Combining Multiple Models for Speech Information Retrieval](http://www.lrec-conf.org/proceedings/lrec2008/pdf/45_paper.pdf) (Alzghool & Inkpen, LREC 2008)

• Combining Multiple Models for Speech Information Retrieval (Alzghool & Inkpen, LREC 2008)

ACL

• Muath Alzghool and Diana Inkpen. 2008. Combining Multiple Models for Speech Information Retrieval. In Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08), Marrakech, Morocco. European Language Resources Association (ELRA).