publication . Contribution for newspaper or weekly magazine . Conference object . 2007

Comparison of HMM and DTW methods in automatic recognition of pathological phoneme pronunciation

Robert Wielgat; Zieliński, T. P.; Świeçtojański, P.; Zoła̧dź, P.; Król, D.; Woźniak, T.; Grabias, S.;
Open Access English
  • Published: 01 Jan 2007
  • Country: United Kingdom
Abstract
In the paper recently proposed Human Factor Cepstral Coefficients (HFCC) are used to automatic recognition of pathological phoneme pronunciation in speech of impaired children and efficiency of this approach is compared to application of the standard Mel-Frequency Cepstral Coefficients (MFCC) as a feature vector. Both dynamic time warping (DTW), working on whole words or embedded phoneme patterns, and hidden Markov models (HMM) are used as classifiers in the presented research. Obtained results demonstrate superiority of combining HFCC features and modified phoneme-based DTW classifier.
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Contribution for newspaper or weekly magazine . 2007
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