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Context Dependent Transformation of Expressivity in Speech Using a Bayesian Network

Type

text
 

Genre(s)

article
 

Forme(s)

document numérique
 

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

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Titre

Context Dependent Transformation of Expressivity in Speech Using a Bayesian Network
 

Nom(s)

Beller, Grégory (auteur)
 

Publication

2007
 

Description

Sujet(s)

emotion   prosody   para linguistique   bayesian   expressivity
 

Résumé

In this paper we describe a transformation system of speech expressivity. It aims at modifying the expressivity of a spoken or synthesized neutral utterance. The phonetic transcription, the stress level and the other information about the corresponding text supply a sequence of contexts. Every context corresponds to a set of parameters of acoustic transformation. These parameters change along the sentence and are used by a phase vocoder technology to transform the speech signal. The relation between the transformation parameters and the contexts is initialized by a set of rules. A Bayesian network transforms gradually this rule-based model into a data-driven model according to a learning phase involving an French expressive database. The system functions for French utterances and several acted emotions. It is employed at artistic ends for the multi-media, the theater and the cinema.
 

Note(s)

Contribution au colloque ou congrès : ParaLing
 

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Date de la notice

2010-02-25 01:00:00
 

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