<abstract xmlns="http://www.w3.org/1999/xhtml"><p> The paper describes our experiment with using the Gaussian mixture models (GMM) for classification of speech uttered by a person wearing orthodontic appliances. For the GMM classification, the input feature vectors comprise the basic and the complementary spectral properties as well as the supra-segmental parameters. Dependence of classification correctness on the number of the parameters in the input feature vector and on the computation complexity is also evaluated. In addition, an influence of the initial setting of the parameters for GMM training process was analyzed. Obtained recognition results are compared visually in the form of graphs as well as numerically in the form of tables and confusion matrices for tested sentences uttered using three configurations of orthodontic appliances.</p></abstract>

The paper describes our experiment with using the Gaussian mixture models (GMM) for classification of speech uttered by a person wearing orthodontic appliances. For the GMM classification, the input feature vectors comprise the basic and the complementary spectral properties as well as the supra-segmental parameters. Dependence of classification correctness on the number of the parameters in the input feature vector and on the computation complexity is also evaluated. In addition, an influence of the initial setting of the parameters for GMM training process was analyzed. Obtained recognition results are compared visually in the form of graphs as well as numerically in the form of tables and confusion matrices for tested sentences uttered using three configurations of orthodontic appliances.

EVALUATION OF SPECTRAL AND PROSODIC FEATURES OF SPEECH AFFECTED BY ORTHODONTIC APPLIANCES USING THE GMM CLASSIFIER

Institute of Measurement Science, Slovak Academy of Sciences, Bratislava, Slovakia

Institute of Electronics and Photonics, Faculty of Electrical Engineering & Information Technology, Slovak University of Technology, Bratislava, Slovakia

Journal of Electrical Engineering

The paper describes our experiment with using the Gaussian mixture models (GMM) for classification of speech uttered by a person wearing orthodontic...

EVALUATION OF SPECTRAL AND PROSODIC FEATURES OF SPEECH AFFECTED BY ORTHODONTIC APPLIANCES USING THE GMM CLASSIFIER

Online veröffentlicht: 14. Feb. 2014

Seitenbereich: 30 - 36

DOI: https://doi.org/10.2478/jee-2014-0004

This content is open access.