No 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.

Abstract. This paper addresses the comparison of Pitch Detection Algorithms working on a cycle to cycle basis. An alignment problem between detected and reference pitch contours is described and a Dynamic Time Warping procedure to correct it is proposed. The method is evaluated using hand-marked real signals and three well known Pitch Detection Algorithms. Results demonstrate the occurrence of shifts in practice and the usefulness of the proposed Dynamic Time Warping procedure.

No abstract

No abstract