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Erschienen in:
2014 | OriginalPaper | Buchkapitel
Quantification of Linear and Non-linear Acoustic Analysis Applied to Voice Pathology Detection
verfasst von : Daria Panek, Andrzej Skalski, Janusz Gajda
Erschienen in: Information Technologies in Biomedicine, Volume 4
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Present development of digital registration and methods of recorded voice processing are useful in detection of most pathologies and diseases of a human vocal tract. The recognition of the voice condition requires the creation of a model which is comprised of different acoustic parameters of speech signal. In this study a vector consisting of 31 parameters for analysing the speech signal was created. The speech parameters were extracted from time, frequency and cepstral domains. Using Principal Components Analysis the number of the parameters was reduced to 17. In order to validate the detection of the pathological voice signal, a tenfold cross-validation and confusion matrix were used. The goal and novelty of this work was the analysis of applicability of the parameters selectively used to assess the pathology.