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Automatic understanding of acoustic speech signal pathology

Wszołek W.

Archives of Acoustics

2007

Vol. 32, No. 1

147-163

In this work, parts of the research concerning a new concept of applying computer technique in pathological speech analysis have been presented. This new concept assumes that during the pathological speech analysis we are not aiming neither at the establishing of such or other signal parameters nor at the trying to classify them, but we tend to understand automatically the causes of deformation, which can be observed in the considered signal. Therefore the concept presented postulates the replacing the well known process of the pathological speech acoustic signal recognition by a more advanced method of analysis, which means a confrontation of the features, which are revealed in the signal during its transformation with features that could be expected basing on the knowledge gathered in the system concerning pathological factors deforming the true form of the signal. In the meaning of the term "automated understanding", this denotes a signal analysis of a deformed speech, which is oriented towards revealing the sources of the observed signal distortions, and not towards bare analysis of their patterns and diagnostic deduction based on their typology. In the work the basic elements of the proposed method are presented. Examples showing its essence were derived basing on the selected larynx pathology analysis.

Selected methods of pathological speech signal analysis

Wszołek W.

Archives of Acoustics

2006

Vol. 31, No. 4

413-430

Selected results of examinations, having been performed by the author for several years, concerning the evaluation of selected methods of transforming signal in analysis tasks and pathological speech evaluation usability were presented in the article. In many issues of medical diagnosis, as well as in the planning of some illnesses therapy and rehabilitation, it is necessary to evaluate the signal of deformed speech. This evaluation can concern evaluation of the signal deformation degree and in this case the task is to present in a quantitative dimension (preferably scalar) the measure of deviation between the measured pathological speech signal and the abstract signal, which can be acknowledged as a pattern of the correct speech. Possessing such a scalar measurement, of the considered signal deformation degree, enables to monitor the illness process development or remission, which has a key importance in the current monitoring of the therapy effects or/and many illnesses rehabilitation. Pathological speech evaluation can also go into the direction of a classification and determination of a type of the analysed signal, which can, in some cases, have a direct connection with anatomical and functional causes as well as conditions of the considered illness. The classification of pathological speech signals can facilitate the diagnosis by pointing the most probable causes of the speech signal pathological deformation. Such a classification can also help in the optimal therapy selection and in determining rehabilitation recommendations. The methods of transformation, analysis, classification and speech signal recognition have been known apparently for many years, as with no difficulty, many writings discussing these concepts and presenting results concerning both basic examinations results and many application works, can be found. The problem, presented in this article, is strongly different from the majority of works, which were published by other authors, as most of well known works, concerning the speech signal analysis (etc.), are directed to understand the content of the statement (automatic speech understanding, a speech-writing conversion, steering of the devices by speech signal), or relatively by determining the identity of the speaker (automatic identification or authentification of the speaker). Meanwhile, in the pathological speech analysis the semantic statement content is not essential; it is also not important who the speaker is. The research subject is the speech articulation process itself and all its pathological deformations, which determines both the used signal analysis tools as well as the techniques of the selected objects recognition, which are the forms of the particular ill person speech deformation forms in comparison to the speech of the whole sound people population [5].