• DocumentCode
    1675022
  • Title

    Voice Pathology Detection Using Vocal Tract Area

  • Author

    Muhammad, Ghulam

  • Author_Institution
    Dept. of Comput. Eng., King Saud Univ., Riyadh, Saudi Arabia
  • fYear
    2013
  • Firstpage
    164
  • Lastpage
    168
  • Abstract
    In this paper, we develop an automatic voice pathology detection (VPD) system based on voice production theory. More specifically, we extract features from vocal tract area function from the tubes, which are closely located to the glottis. Voice pathology is related to a vocal fold problem, and hence the vocal tract area connected to the vocal fold or the glottis should exhibit irregular patterns over frames in case of a sustained vowel for a pathological voice. This irregular pattern is quantified in the form of variance across the frames to distinguish between normal and pathological voices. The proposed VPD system is evaluated on the MEEI database with sustained vowel samples and achieves 99.02%±0.01 accuracy.
  • Keywords
    feature extraction; medical computing; medical disorders; patient diagnosis; speech; speech processing; support vector machines; MEEI database; automatic voice pathology detection system; feature extraction; glottis; tubes; vocal tract area function; voice production theory; vowel samples; Accuracy; Databases; Electron tubes; Feature extraction; Pathology; Speech; Support vector machines; support vector machines; vocal tract area; voice disorders; voice pathology detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Modelling Symposium (EMS), 2013 European
  • Conference_Location
    Manchester
  • Print_ISBN
    978-1-4799-2577-3
  • Type

    conf

  • DOI
    10.1109/EMS.2013.29
  • Filename
    6779840