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  • Research Article
  • Open Access

On the Use of the Correlation between Acoustic Descriptors for the Normal/Pathological Voices Discrimination

  • 1Email author,
  • 1,
  • 1 and
  • 2
EURASIP Journal on Advances in Signal Processing20092009:173967

  • Received: 27 October 2008
  • Accepted: 23 April 2009
  • Published:


This paper presents an analysis system aiming at discriminating between normal and pathological voices. Compared to literature of voice pathology assessment, it is characterised by two aspects. First the system is based on features inspired from voice pathology assessment and music information retrieval. Second the distinction between normal and pathological voices is simply based on the correlation between acoustic features, while more complex classifiers are common in literature. Based on the normal and pathological samples included the MEEI database, it has been found that using two features (spectral decrease and first spectral tristimulus in the Bark scale) and their correlation leads to correct classification rates of 94.7% for pathological voices and 89.5% for normal ones. The system also outputs a normal/pathological factor aiming at giving an indication to the clinician about the location of a subject according to the database.


  • Information Technology
  • Bark
  • Information Retrieval
  • Quantum Information
  • Classification Rate

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Authors’ Affiliations

TCTS Lab, Faculté Polytechnique de Mons, 31 Boulevard Dolez, 7000 Mons, Belgium
ORL-ORLO Lab, Université Catholique de Louvain, Avenue Dr Therasse, 8, 5530 Yvoir, Belgium


© Thomas Dubuisson et al. 2009

This article is published under license to BioMed Central Ltd. 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.