Improving Dysarthria Classification by Pattern Recognition Techniques Based on a Bionic Model

Abstract

The goal of this research is to use a bionic model to enhance classification of Dysarthria. The model based on the main features of the mammalian olfactory system is the initial stage of the recognition process. The bionic model aimed to achieve an enhancement in the separation ability of the dysarthric features. The recognition performance obtained by four different pattern recognition algorithms using the bionic model to improve the features is shown and discussed. The results indicated that bionic model had clear influence on classification performance of well-known techniques using dysarthria database as case study. We regard the results of this study as a promising initial step to the use of bionic model as a recognition improvement function.

Speech signal analysis and pattern recognition in diagnosis of dysarthria

“…Dysarthria refers to a group of speech disorders resulting from disturbances in muscular control over the speech mechanism due to damage of the central or peripheral nervous system. [ 1 ] Although there have been several attempts to improve speech recognition for dysarthric speakers, and other attempts to integrate articulatory knowledge into speech recognition, these efforts have not until recently converged. There is wide subjective variability in assessment of dysarthria between different clinicians.…”

A study of quantitative and qualitative analysis of standardized speech samples in persons suffering from dysarthria due to various neurological disorder

“…3 Formant analysis which is considered as a function of vocal tract can be affected by deficits in articulatory control and mobility of the same. 4 Zwirner and Barnes reported increased variability of first formant (F1) values during vowel prolongations. 5 Speakers with Parkinson's disease (PD) were found to have reduced F1-F2 vowel space, compared to control speakers.…”