Abstract
The diagnosis of the current state of the vocal tract requires the creation of a feature vector that consists of various acoustic parameters, which can help in rapid and automatic detection of voice pathologies. Vector consisting of 31 parameters was done in this project. Speech parameters were extracted in the time, frequency and cepstral domain. Essential parameters were selected and analysed using principal component analysis, kernel principal component analysis and linear discriminant analysis. (Parameters evaluation of acoustic analysis in speech pathology detection)
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