• DocumentCode
    3116097
  • Title

    Pathological Voice Assessment

  • Author

    Dibazar, Alireza A. ; Berger, Theodore W. ; Narayanan, Shrikanth S.

  • Author_Institution
    Dept. of Biomed. Eng., Univ. of Southern California, Los Angeles, CA
  • fYear
    2006
  • fDate
    Aug. 30 2006-Sept. 3 2006
  • Firstpage
    1669
  • Lastpage
    1673
  • Abstract
    While there are number of guidelines and methods used in practice, there is no standard universally agreed upon system for assessment of pathological voices. Pathological voices are primarily labeled based on the perceptual judgments of specialists, a process that may result in different label(s) being assigned to a given voice sample. This paper focuses on the recognition of five specific pathologies. The main goal is to compare two different classification methods. The first method considers single label classification by assigning a new label (single label) to the ensembles to which they most likely belong. The second method employs all labels originally assigned to the voice samples. Our results show that the pathological voice assessment performance in the second method is improved with respect to the first method
  • Keywords
    cepstral analysis; diseases; hidden Markov models; maximum likelihood estimation; pattern classification; speech recognition; Mel frequency cepstral coefficients; anterior-posterior squeezing; classification methods; gastric reflux; hidden Markov model; hyper-function; maximum a posteriori estimation; multiclass recognition; paralysis; pathological voice assessment; pathology recognition; perceptual judgment; single label classification; speech analysis; ventricular compression; Acoustic measurements; Biomedical engineering; Biomedical measurements; Cities and towns; Electric variables measurement; Frequency measurement; Laboratories; Pathology; Speech analysis; Speech recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, 2006. EMBS '06. 28th Annual International Conference of the IEEE
  • Conference_Location
    New York, NY
  • ISSN
    1557-170X
  • Print_ISBN
    1-4244-0032-5
  • Electronic_ISBN
    1557-170X
  • Type

    conf

  • DOI
    10.1109/IEMBS.2006.259835
  • Filename
    4462091