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Authors: Abdenour Hacine-Gharbi 1 ; Philippe Ravier 2 and François Nemo 2

Affiliations: 1 University of Bordj Bou Arréridj, Algeria ; 2 University of Orleans, France

ISBN: 978-989-758-222-6

Keyword(s): Prosodic Classification, Local and Global Prosodic Features, Dimensionality Reduction, Curse of Dimensionality, Filter Feature Selection, Mutual Information, Classification of Word’s Uses.

Related Ontology Subjects/Areas/Topics: Applications ; Artificial Intelligence ; Classification ; Feature Selection and Extraction ; Knowledge Engineering and Ontology Development ; Knowledge-Based Systems ; Natural Language Processing ; Pattern Recognition ; Symbolic Systems ; Theory and Methods

Abstract: The aim of this study is to evaluate the ability of local or global prosodic features in achieving a classification task of word’s uses. The use of French word “oui” in spontaneous discourse can be identified as belonging to the class “convinced (CV)”or “lack of conviction (NCV)”. Statistics of classical prosodic patterns are considered for the classification task. Local features are those computed on single phonemes. Global features are computed on the whole word. The results show that 10 features completely explain the two clusters CV and NCV carried out by linguistic experts, the features having being selected thanks to the Max-Relevance Min-Redundancy filter selection strategy. The duration of the phoneme /w/ is found to be highly relevant for all the investigated classification systems. Local features are predominantly more relevant than global ones. The system was validated by building classification systems in a speaker dependent mode and in a speaker independent mode and also by investigating manual phoneme segmentation and automatic phoneme segmentation. In the most favorable case (speaker dependent mode and manual phoneme segmentation), the rate reached 87.72%. The classification rate reached 78.57% in the speaker independent mode with automatic phoneme segmentation which is a system configuration close to an industrial one. (More)

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Paper citation in several formats:
Hacine-Gharbi, A.; Ravier, P. and Nemo, F. (2017). Local and Global Feature Selection for Prosodic Classification of the Word’s Uses.In Proceedings of the 6th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-222-6, pages 711-717. DOI: 10.5220/0006251407110717

@conference{icpram17,
author={Abdenour Hacine{-}Gharbi. and Philippe Ravier. and Fran\c{C}ois Nemo.},
title={Local and Global Feature Selection for Prosodic Classification of the Word’s Uses},
booktitle={Proceedings of the 6th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2017},
pages={711-717},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006251407110717},
isbn={978-989-758-222-6},
}

TY - CONF

JO - Proceedings of the 6th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - Local and Global Feature Selection for Prosodic Classification of the Word’s Uses
SN - 978-989-758-222-6
AU - Hacine-Gharbi, A.
AU - Ravier, P.
AU - Nemo, F.
PY - 2017
SP - 711
EP - 717
DO - 10.5220/0006251407110717

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