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Analysis and Automatic Classification of Some Discourse Particles on a Large Set of French Spoken Corpora

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Book cover Statistical Language and Speech Processing (SLSP 2017)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10583))

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Abstract

In French, quite a number of words and expressions are frequently used as discourse particles in spoken language, especially in spontaneous speech. The semantic load of these words or expressions differ whether they are used as discourse particles or not. Therefore, the correct identification of their discourse function remains of great importance. In this paper the distribution of the discourse function (or not discourse function), and of the detailed discourse functions of some of these words, is studied on a large set of French corpora ranging from prepared speech (e.g. storytelling and broadcast news) to spontaneous speech (e.g. interviews and interactions between people). The paper is focused on a subset of discourse particles that are recurrent in the considered corpora. The discourse function of a few thousand occurrences of these words have been manually annotated. A statistical analysis of the functions of the words is presented and discussed with respect to the types of spoken corpora. Finally, some statistics with respect to a few prosodic correlates of the discourse particles are presented, as well as some results of automatic classification and detection of the word function (discourse particle or not) using prosodic features.

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Acknowledgments

This work has been carried out in the framework of the ProsodCorpus operation supported by the CPER LCHN (Contrat Plan Etat Région “Langues, Connaissances et Humanités Numériques”). Some experiments presented in this paper have been carried out using the Grid’5000 testbed, supported by a scientific interest group hosted by Inria and including CNRS, RENATER and several Universities as well as other organizations (see https://www.grid5000.fr).

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Authors and Affiliations

  1. Inria, 54600, Villers-lès-Nancy, France

    Denis Jouvet

  2. Université de Lorraine, LORIA, UMR 7503, 54600, Villers-lè-Nancy, France

    Denis Jouvet

  3. CNRS, LORIA, UMR 7503, 54600, Villers-lès-Nancy, France

    Denis Jouvet

  4. Université de Lorraine, ATILF, UMR 7118, 54063, Nancy, France

    Katarina Bartkova, Mathilde Dargnat & Lou Lee

  5. CNRS, ATILF, UMR 7118, 54063, Nancy, France

    Katarina Bartkova, Mathilde Dargnat & Lou Lee

Authors
  1. Denis Jouvet
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  2. Katarina Bartkova
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  3. Mathilde Dargnat
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  4. Lou Lee
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Corresponding author

Correspondence to Denis Jouvet .

Editor information

Editors and Affiliations

  1. University of Le Mans, Le Mans, France

    Nathalie Camelin

  2. University of Le Mans, Le Mans, France

    Yannick Estève

  3. Rovira i Virgili University, Tarragona, Spain

    Carlos Martín-Vide

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Jouvet, D., Bartkova, K., Dargnat, M., Lee, L. (2017). Analysis and Automatic Classification of Some Discourse Particles on a Large Set of French Spoken Corpora. In: Camelin, N., Estève, Y., Martín-Vide, C. (eds) Statistical Language and Speech Processing. SLSP 2017. Lecture Notes in Computer Science(), vol 10583. Springer, Cham. https://doi.org/10.1007/978-3-319-68456-7_3

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  • DOI: https://doi.org/10.1007/978-3-319-68456-7_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-68455-0

  • Online ISBN: 978-3-319-68456-7

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