• DocumentCode
    3307397
  • Title

    The methods of pathological speech visualization [using Kohonen neural networks]

  • Author

    Tadeusiewicz, R. ; Wszolek, W. ; Izworski, Antoni ; Wszolek, T.

  • Author_Institution
    Dept. of Autom., Univ. of Min. & Metall., Krakow, Poland
  • Volume
    2
  • fYear
    1999
  • fDate
    36434
  • Abstract
    In tasks related to the analysis and recognition of pathological speech it is often more important to provide the respective person (e.g. physician) with guidelines for a qualitative evaluation of this speech than to achieve a very accurate automated recognition. By ear it is easy to judge whether the speech is regular or deformed, but any attempt of a quantitative evaluation is not satisfactory. If the speech is transformed to a graphic form, by a proper visualization method, it is easier for a person to estimate its deformation degree by comparing the respective graphical patterns. The new visualization method proposed is based on the results obtained by application of Kohonen neural networks
  • Keywords
    medical signal processing; pattern classification; self-organising feature maps; signal classification; speech processing; speech recognition; Kohonen neural networks; articulation; graphical patterns; pathological speech visualization; qualitative evaluation; signal registration multi-spectrum; speech analysis; speech recognition; winner neurons; Automatic speech recognition; Data visualization; Ear; Gold; Neural networks; Pathology; Signal processing; Speech analysis; Speech processing; Speech recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    [Engineering in Medicine and Biology, 1999. 21st Annual Conference and the 1999 Annual Fall Meetring of the Biomedical Engineering Society] BMES/EMBS Conference, 1999. Proceedings of the First Joint
  • Conference_Location
    Atlanta, GA
  • ISSN
    1094-687X
  • Print_ISBN
    0-7803-5674-8
  • Type

    conf

  • DOI
    10.1109/IEMBS.1999.804134
  • Filename
    804134