A Syllable-Based Prominence Detection Model Based on Discriminant Analysis and Context-Dependency - HAL-SHS - Sciences de l'Homme et de la Société Accéder directement au contenu
Communication Dans Un Congrès Année : 2009

A Syllable-Based Prominence Detection Model Based on Discriminant Analysis and Context-Dependency

Résumé

On the basis of our previous work, we propose a syllablebased prominence detection model within the framework of exploratory data analysis and discriminant learning in the acoustic domain. This paper investigates two hypothesis on the acoustic data processing: a linear discriminant analysis in which the relative discriminant ability of single prosodic cues are combined into prosodic patterns and a context-dependant model that accounts for phonological dependencies (phonetic intrinsic properties and coarticulation effect). The proposed approach significantly outperforms a baseline method on a corpus of French read speech with a performance of 87.5% in f-measure for the prominent syllables (respectively 90.4% in global accuracy).

Mots clés

Domaines

Linguistique
Fichier principal
Vignette du fichier
20.SpeCom.pdf (95.95 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

halshs-00636518 , version 1 (18-11-2011)

Identifiants

  • HAL Id : halshs-00636518 , version 1

Citer

Nicolas Obin, Xavier Rodet, Anne Lacheret-Dujour. A Syllable-Based Prominence Detection Model Based on Discriminant Analysis and Context-Dependency. Speech and Computer, 2009, Russia. pp.97-100. ⟨halshs-00636518⟩
157 Consultations
82 Téléchargements

Partager

Gmail Facebook X LinkedIn More