Authors:
Abdenour Hacine-Gharbi
1
and
Philippe Ravier
2
Affiliations:
1
LMSE Laboratory, University of Bordj Bou Arréridj, Elanasser, 34030 Bordj Bou Arréridj, Algeria
;
2
PRISME Laboratory, University of Orleans, 12 Rue de Blois, 45067 Orleans, France
Keyword(s):
Speech Injunction Classification, Massive Wild Oral Corpus, Feature Extraction, Wrapper Feature Selection, Prosodic Features, Static and Dynamic Features, GMM Models.
Abstract:
The injunctive values are of particular interest for many studies dealing with oral speech interactions, e.g. in automatic meaning processing or in the field of language pathology understanding and therapy. We propose in this paper an automatic classification system using a subset of the RAVIOLI database in order to evaluate the role of prosody in the definition of injunctive values. RAVIOLI is constituted of more than 100 hours wild massive oral spontaneous speech. This work is a preliminary study that exploits a subset of 197 injunction values that have been labelled as exploitable utterances by two linguistic experts augmented by 198 of non-injunctive utterances. Many feature types were considered for this study: some classical features employed in speech community for automatic speech recognition tasks (LPCC, MFCC and PLP with their associated dynamic features) and some prosodic features (pitch and energy, with their associated dynamic features). The results clearly show the impo
rtance of prosodic features for the classification of the utterances into injunction or no-injunction classes and particularly the predominance of the log energy feature.
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