• DocumentCode
    472163
  • Title

    Acoustic Speech Analysis for Hypernasality Detection in Children

  • Author

    Castellanos, G. ; Daza, G. ; Sanchez, L. ; Castrillon, O. ; Suarez, J.

  • Author_Institution
    Univ. Nacional de Colombia Sede Manizales, Columbia, SC
  • fYear
    2006
  • fDate
    Aug. 30 2006-Sept. 3 2006
  • Firstpage
    5507
  • Lastpage
    5510
  • Abstract
    Here, an analysis of different acoustic features and their influence in automatic identification of hypernasality is shown. Effective feature selection method includes preprocessing of the initial feature space based on statistical independence analysis. Simultaneously, the synthesis of a specialized diagnostic feature is proposed based on analyzing the acoustic emission of the hyper nasal speech. As a result, It is obtained the acoustic features can differentiate with enough precision the pathology. However, the proposed feature does not require training samples and less computational power, as well
  • Keywords
    paediatrics; speech processing; statistical analysis; acoustic emission analysis; acoustic speech analysis; automatic identification; children; feature selection method; hypernasal speech; hypernasality detection; pathology; precision; specialized diagnostic feature; statistical independence analysis; Acoustic distortion; Acoustic emission; Acoustic signal detection; Cities and towns; Pathology; Resonance; Speech analysis; Speech enhancement; Speech synthesis; Surgery;
  • 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.2006.260572
  • Filename
    4463052