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.
|Title of host publication||INTERSPEECH 2007, 8th Annual Conference of the International Speech Communication Association, Antwerp, Belgium, August 27-31, 2007|
|Number of pages||4|
|Publication status||Published - 2007|
|Event||8th Annual Conference of the International Speech Communication Association - Antwerp, Belgium|
Duration: 27 Aug 2007 → 31 Aug 2007
|Conference||8th Annual Conference of the International Speech Communication Association|
|Period||27/08/07 → 31/08/07|