International Conference on Statistical Language and Speech Processing

Statistical Language and Speech Processing pp 39-49

Discourse Particles in French: Prosodic Parameters Extraction and Analysis

  • Mathilde Dargnat
  • Katarina Bartkova
  • Denis Jouvet
Conference paper

DOI: 10.1007/978-3-319-25789-1_5

Part of the Lecture Notes in Computer Science book series (LNCS, volume 9449)
Cite this paper as:
Dargnat M., Bartkova K., Jouvet D. (2015) Discourse Particles in French: Prosodic Parameters Extraction and Analysis. In: Dediu AH., Martín-Vide C., Vicsi K. (eds) Statistical Language and Speech Processing. Lecture Notes in Computer Science, vol 9449. Springer, Cham

Abstract

Detecting the correct syntactic function of a word is of great importance for language and speech processing. The semantic load of a word is different whether its function is a discourse particle or a preposition. Words having the function of a discourse particle (DP) are very frequent in spontaneous speech and their discursive function is often expressed only by prosodic means. Our study analyses some prosodic correlates of two French words (quoi, voilà), used as discourse particles or pronoun (quoi) or preposition (voilà). Our goal is to determine to what extent intrinsic and contextual prosodic properties characterize DP and non-DP functions. Prosodic parameters are analyzed with respect to the DP or non-DP function for these words extracted from large speech corpora. A preliminary test concerning the automatic detection of the word function is also carried out using prosodic parameters only, leading to an encouraging result of 70 % correct identification.

Keywords

Part-of-speech tagging Prosody Discourse particles  Discourse structure Automatic prosodic annotation 

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Mathilde Dargnat
    • 1
  • Katarina Bartkova
    • 1
  • Denis Jouvet
    • 2
    • 3
    • 4
  1. 1.Université de Lorraine & CNRS, ATILF, UMR 7118Nancy CedexFrance
  2. 2.Speech GroupInria, LORIAVillers-lès-NancyFrance
  3. 3.Université de Lorraine, LORIA, UMR 7503Villers-lès-NancyFrance
  4. 4.CNRS, LORIA, UMR 7503Villers-lès-NancyFrance

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