This article is part of the series Analysis and Signal Processing of Oesophageal and Pathological Voices.

Open Access Research Article

Back-and-Forth Methodology for Objective Voice Quality Assessment: From/to Expert Knowledge to/from Automatic Classification of Dysphonia

Corinne Fredouille1*, Gilles Pouchoulin1, Alain Ghio2, Joana Revis2, Jean-François Bonastre1 and Antoine Giovanni2

Author Affiliations

1 Laboratoire Informatique d'Avignon (LIA), University of Avignon, 84911 Avignon, France

2 LPL-CNRS, Aix-Marseille University, 13604 Aix-en-Provence, France

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EURASIP Journal on Advances in Signal Processing 2009, 2009:982102  doi:10.1155/2009/982102


The electronic version of this article is the complete one and can be found online at: http://asp.eurasipjournals.com/content/2009/1/982102


Received: 31 October 2008
Revisions received: 1 April 2009
Accepted: 10 June 2009
Published: 19 July 2009

© 2009 The Author(s).

This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

This paper addresses voice disorder assessment. It proposes an original back-and-forth methodology involving an automatic classification system as well as knowledge of the human experts (machine learning experts, phoneticians, and pathologists). The goal of this methodology is to bring a better understanding of acoustic phenomena related to dysphonia. The automatic system was validated on a dysphonic corpus (80 female voices), rated according to the GRBAS perceptual scale by an expert jury. Firstly, focused on the frequency domain, the classification system showed the interest of 0–3000 Hz frequency band for the classification task based on the GRBAS scale. Later, an automatic phonemic analysis underlined the significance of consonants and more surprisingly of unvoiced consonants for the same classification task. Submitted to the human experts, these observations led to a manual analysis of unvoiced plosives, which highlighted a lengthening of VOT according to the dysphonia severity validated by a preliminary statistical analysis.

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