musique contemporaine

Ircam - articles scientifiques notice originale

French Prominence: A Probabilistic Framework

Type

text
 

Genre(s)

article
 

Forme(s)

document numérique
 

Cette ressource est disponible chez l'organisme suivant : Ircam - Centre Pompidou

Identification

Titre

French Prominence: A Probabilistic Framework
 

Nom(s)

Obin, Nicolas (auteur)
 
Rodet, Xavier (auteur)
 
Lacheret, Anne (auteur)
 

Publication

Las Vegas, USA , 2008
 

Description

Sujet(s)

Prosody   prominence   acoustic correlates   feature selection   classification   GMMl
 

Résumé

Identification of prosodic phenomena is of first importance in prosodic analysis and modeling. In this paper, we introduce a new method for automatic prosodic phenomena labelling. The authors set their approach of prosodic phenomena in the framework of prominence. The proposed method for automatic prominence labelling is based on well-known machine learning techniques in a three step procedure: i) a feature extraction step in which we propose a framework for systematic and multi-level speech acoustic feature extraction, ii) a feature selection step for identifying the more relevant prominence acoustic correlates, and iii) a modelling step in which a gaussian mixture model is used for predicting prominence. This model shows robust performance on read speech (84%).
 

Note(s)

Contribution au colloque ou congrès : International Conference on Acoustics, Speech, and Signal Processing (ICASSP)
 

Localisation

Envoyer la notice

Bookmark and Share 
 

Identifiant OAI

 

Date de la notice

2012-08-09 02:00:00
 

Identifiant portail

 

Contact