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National Repository of Grey Literature 2 records found  Search took 0.01 seconds. 
Cluster analysis in the field of pathological speech signal processing
 Čapek, Karel ; Mžourek, Zdeněk (referee) ; Galáž, Zoltán (advisor)
The bachelor thesis deals with the calculation of speech features that quantifies the degradation of speech production caused by the presence of certain speech pathology and the subsequent clasification of considered speech pathologies into several groups using the k-means algorithm. The purpose was to find the groups of pathologies that in spite of possible differences in the origin do affect phonation and articulation skills of the speakers and damage the quality of speech. The work uses the phonation of vowels "a" speech task as the most commonly used speech task in the field of pathological speech processing, because of its resistance to demographic and linguistic characteristics of the speakers. Furthermore, the preliminary analysis was applied to the featuresin order to select the features to best characterize the degradation of speech production. Finally, the selected features were used to find the resulting groups of pathologies using k-means algorithm.
Detailed record
Cluster analysis in the field of pathological speech signal processing
 Čapek, Karel ; Mžourek, Zdeněk (referee) ; Galáž, Zoltán (advisor)
The bachelor thesis deals with the calculation of speech features that quantifies the degradation of speech production caused by the presence of certain speech pathology and the subsequent clasification of considered speech pathologies into several groups using the k-means algorithm. The purpose was to find the groups of pathologies that in spite of possible differences in the origin do affect phonation and articulation skills of the speakers and damage the quality of speech. The work uses the phonation of vowels "a" speech task as the most commonly used speech task in the field of pathological speech processing, because of its resistance to demographic and linguistic characteristics of the speakers. Furthermore, the preliminary analysis was applied to the featuresin order to select the features to best characterize the degradation of speech production. Finally, the selected features were used to find the resulting groups of pathologies using k-means algorithm.
Detailed record

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