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Discourse Particles In French: Prosodic Parameters Extraction and Analysis

Mathilde Dargnat 1 Katarina Bartkova 1 Denis Jouvet 2, *
* Corresponding author
2 MULTISPEECH - Speech Modeling for Facilitating Oral-Based Communication
Inria Nancy - Grand Est, LORIA - NLPKD - Department of Natural Language Processing & Knowledge Discovery
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,voiì a), used as discourse particles or pronoun (quoi) or preposition (voiì a). 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.
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Mathilde Dargnat, Katarina Bartkova, Denis Jouvet. Discourse Particles In French: Prosodic Parameters Extraction and Analysis. International Conference on Statistical Language and Speech Processing, Nov 2015, Budapest, Hungary. ⟨hal-01184197⟩

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