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

Robert Wielgat, Tomasz P. Zieliński, Paweł Świętojański, Piotr Żołądź, Daniel Król, Tomasz Woźniak, Stanisław Grabias
2007 Interspeech 2007   unpublished

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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
more » ... demonstrate superiority of combining HFCC features and modified phoneme-based DTW classifier.
doi:10.21437/interspeech.2007-479 fatcat:ohlj5l3vpndtfjfxcrvx5o7ss4
Citation

Robert Wielgat, Tomasz P. Zieliński, Paweł Świętojański, Piotr Żołądź, Daniel Król, Tomasz Woźniak, Stanisław Grabias. "Comparison of HMM and DTW methods in automatic recognition of pathological phoneme pronunciation." Interspeech 2007 (2007)