@inproceedings{,
author={Kocsor, Andr{\'a}s and T{\'o}th, L{\'a}szl{\'o} and Paczolay, D{\'e}nes},
title={A Nonlinearized Discriminant Analysis and its Application to Speech Impediment
Therapy},
abstract={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.},
booktitle={Text, Speech and Dialogue : 4th International Conference, TSD 2001, LNAI
vol. 2166},
year={2001},
month={September},
publisher={Springer-Verlag GmbH},
address={Zelezna Ruda, Czech Republic},
editor={V. Matouek, P. Mautner, R. Mouek, K. Tauer },
pages={249-257}
}