A Nonlinearized Discriminant Analysis and its Application to Speech Impediment Therapy
|Title||A Nonlinearized Discriminant Analysis and its Application to Speech Impediment Therapy|
|Publication Type||Conference Paper|
|Year of Publication||2001|
|Authors||Kocsor A, Tóth L, Paczolay D|
|Conference Name||Text, Speech and Dialogue : 4th International Conference, TSD 2001, LNAI vol. 2166|
|Place Published||Zelezna Ruda, Czech Republic|
This paper studies the application of automatic phoneme classification to the computer-aided training of the speech and hearing handicapped. In particular, we focus on how efficiently discriminant analysis can reduce the number of features and increase classification performance. A nonlinear counterpart of Linear Discriminant Analysis, which is a general purpose class specific feature extractor, is presented where the nonlinearization is carried out by employing the so-called 'kernel-idea'. Then, we examine how this nonlinear extraction technique affects the efficiency of learning algorithms such as Artificial Neural Network and Support Vector Machines.