Automatic Detection of Disorders in a Continuous Speech with the Hidden Markov Models Approach

  • Marek Wiśniewski
  • Wieslawa Kuniszyk-Jóźkowiak
  • Elzbieta Smołka
  • Waldemar Suszyński
Part of the Advances in Soft Computing book series (AINSC, volume 45)


Hidden Markov Models are widely used for recognition of any patterns appearing in an input signal. In the work HMM’s were used to recognize two kind of speech disorders in an acoustic signal: prolongation of fricative phonemes and blockades with repetition of stop phonemes.


Window Size Acoustic Signal Automatic Detection Probability Threshold Frame Length 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Marek Wiśniewski
    • 1
  • Wieslawa Kuniszyk-Jóźkowiak
    • 1
  • Elzbieta Smołka
    • 1
  • Waldemar Suszyński
    • 1
  1. 1.Institute of Computer ScienceMaria Curie-Sklodowska UniversityLublinPoland

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