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Combining Lexical and Prosodic Features for Automatic Detection of Sentence Modality in French

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Statistical Language and Speech Processing (SLSP 2015)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9449))

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Abstract

This article analyzes the automatic detection of sentence modality in French using both prosodic and linguistic information. The goal is to later use such an approach as a support for helping communication with deaf people. Two sentence modalities are evaluated: questions and statements. As linguistic features, we considered the presence of discriminative interrogative patterns and two log-likelihood ratios of the sentence being a question rather than a statement: one based on words and the other one based on part-of-speech tags. The prosodic features are based on duration, energy and pitch features estimated over the last prosodic group of the sentence. The evaluations consider using linguistic features stemming from manual transcriptions or from an automatic speech transcription system. The behavior of various sets of features are analyzed and compared. The combination of linguistic and prosodic features gives a slight improvement on automatic transcriptions, where the correct classification performance reaches 72 %.

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Acknowledgements

The work presented in this article is part of the RAPSODIE project, and has received support from the “Conseil Régional de Lorraine” and from the “Région Lorraine” (FEDER) (http://erocca.com/rapsodie).

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Authors and Affiliations

  1. Speech Group, Inria, LORIA, 54600, Villers-lès-Nancy, France

    Luiza Orosanu & Denis Jouvet

  2. Speech Group, LORIA, Université de Lorraine, LORIA, UMR 7503, 54600, Villers-lès-Nancy, France

    Luiza Orosanu & Denis Jouvet

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

    Luiza Orosanu & Denis Jouvet

Authors
  1. Luiza Orosanu
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  2. Denis Jouvet
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Correspondence to Luiza Orosanu .

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Editors and Affiliations

  1. Research Group on Mathematical Linguistic, Rovira i Virgili University, Tarragona, Spain

    Adrian-Horia Dediu

  2. Research Group on Mathematical Linguistic, Rovira i Virgili University, Tarragona, Spain

    Carlos Martín-Vide

  3. Department of Telecommunications and Media Informatics, Budapest University of Technology and Economics, Budapest, Hungary

    Klára Vicsi

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Orosanu, L., Jouvet, D. (2015). Combining Lexical and Prosodic Features for Automatic Detection of Sentence Modality in French. In: Dediu, AH., Martín-Vide, C., Vicsi, K. (eds) Statistical Language and Speech Processing. SLSP 2015. Lecture Notes in Computer Science(), vol 9449. Springer, Cham. https://doi.org/10.1007/978-3-319-25789-1_20

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  • DOI: https://doi.org/10.1007/978-3-319-25789-1_20

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-25788-4

  • Online ISBN: 978-3-319-25789-1

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