Automated understanding of selected voice tract pathologies based on the speech signal analysis

In the present work excerpts of research are presented, concerning the application of modified acoustic signal processing methods in the problem of "understanding" of selected pathologies of vocal tract. The presented concept of the research scheme is based on the technique of advanced acoustic signal analysis and it refers to the analysis of artificial neural networks functioning in the task of recognition of selected types of vocal tract pathologies. It is recommended here that the simple process of signal recognition should be replaced by a more advanced method or its analysis, called the process of automated understanding of the signal. The method is based on utilization of an internal model of the considered signal's generator and it is directed towards such a structure analysis of the examined sound, which enables its identification as a result of cognitive resonance. The described method allows to achieve more subtle differentiation for signal characterized by small diversification of measurable features, observed for the classes being recognized, what is the case in the problem or identification of selected pathologies considered here. The circumstances mentioned above suggest a consideration of more knowledge-based approach to the discrimination of acoustic signals, labeled here as a technique of signal understanding.