• DocumentCode
    723333
  • Title

    Discrimination between pathological voice categories using matching pursuit

  • Author

    Kumar, Ashwini Jaya ; Daoudi, Khalid

  • Author_Institution
    Bordeaux-Sud Ouest, INRIA, France
  • fYear
    2015
  • fDate
    10-12 June 2015
  • Firstpage
    215
  • Lastpage
    218
  • Abstract
    There are several methods in the literature for pathological voice classification but there are very few methods which can classify pathological sub-groups. An attempt is made here to classify pathological sub-groups using matching pursuit decomposition method and is compared with PRAAT. Random forest classifier is used and frequency band of the atoms are used as feature. The result shows that we can classify adductor spasmodic dysphonia, keratosis and vocal nodules in a class of voices consisting of adductor spasmodic dysphonia, keratosis, paralysis, vocal nodules and vocal fold polyps with reasonably good classification accuracy. Both matching pursuit (MP) and PRAAT shows comparable classification scores but using MP is more advantageous over PRAAT since it doesn´t rely on pitch information and extraction of pitch information in a pathological signal is a complex problem.
  • Keywords
    feature extraction; iterative methods; medical signal processing; random processes; signal classification; speech processing; time-frequency analysis; PRAAT; adductor spasmodic dysphonia; frequency band; keratosis; matching pursuit decomposition; paralysis; pathological signal; pathological sub-groups; pathological voice classification; pitch extraction; random forest classifier; vocal fold polyps; vocal nodules; Atomic clocks; Databases; Feature extraction; Jitter; Matching pursuit algorithms; Pathology; Time-frequency analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Bioinspired Intelligence (IWOBI), 2015 4th International Work Conference on
  • Conference_Location
    San Sebastian
  • Print_ISBN
    978-1-4673-7845-1
  • Type

    conf

  • DOI
    10.1109/IWOBI.2015.7160169
  • Filename
    7160169