A Method for Automatic and Dynamic Estimation of Discourse Genre. Typology with Prosodic Features

Nicolas Obin (1) , Anne Lacheret (2) , Christophe Veaux (1) , Xavier Rodet (1) , Anne-Catherine Simon (3)

1 STMS - Sciences et Technologies de la Musique et du Son
2 MoDyCo - Modèles, Dynamiques, Corpus
3 Centre de recherche Valibel

This paper presents a work-in-progress on the automatic analysis of discourse genre in non-elicited speech. The study is focused on the development of bottom-up methods for automatic validation of discourse typologies found in linguistic descriptions (prosodic, syntactic, pragmatic and/or contextual and situational cues). The linguistic classification examined here opposes five discourse genres +/- controlled. To test this a priori classification under prosodic criteria, we propose a method that provides an automatic and dynamic estimation of discourse genre typology i.e. of prosodic similarities between discourse genres. This is achieved in a two-step procedure : a set of discriminant prosodic patterns is estimated and then used to raise a typology of discourse genres based on prosodic similarity criterion. The discriminant analysis reveals that a small number of prosodic patterns is sufficient to discriminate the 5 discourse genres. The typological analysis reveals some multi-level caterogical oppositions on a continuous prosodic scale that can be interpreted in terms of +/- controlled speech.

Mots clés: Discourse genre; Prosody; Typology; Discriminant analysis; Agglomerative clustering

Domaines: Linguistique

Nicolas Obin, Anne Lacheret, Christophe Veaux, Xavier Rodet, Anne-Catherine Simon. A Method for Automatic and Dynamic Estimation of Discourse Genre. Typology with Prosodic Features. 9th Annual Conference of the International Speech Communication Association 2008 (INTERSPEECH 2008), Sep 2008, Brisbane, Australia. pp.1204-1207. ⟨halshs-00334345⟩