How to reduce dimension while improving performance

0Citations
Citations of this article
4Readers
Mendeley users who have this article in their library.
Get full text

Abstract

This paper addresses the feature subset selection for an automatic Arabic speaker recognition system. An effective algorithm based on genetic algorithm is proposed for discovering the best feature combinations using feature reduction and recognition error rate as performance measure. Experimentation is carried out using QSDAS corpora. The results of experiments indicate that, with the optimized feature subset, the performance of the system is improved. Moreover, the speed of recognition is significantly increased, number of features is reduced over 60% which consequently decrease the complexity of our ASR system. © 2012 Springer-Verlag.

Cite

CITATION STYLE

APA

Harrag, A., Saigaa, D., Bouchelaghem, A., Drif, M., Zeghlache, S., & Harrag, N. (2012). How to reduce dimension while improving performance. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7208 LNAI, pp. 497–508). https://doi.org/10.1007/978-3-642-28942-2_45

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free