The application of polynomial discriminant function classifiers to isolated arabic speech recognition

Document Type

Conference Proceeding

Source of Publication

IEEE International Conference on Neural Networks - Conference Proceedings

Publication Date

12-1-2004

Abstract

In this paper, we apply polynomial discriminant function classifiers for isolated-word speaker-independent Arabic digit recognition. The performance of the polynomial classifier is evaluated for different implementations. We also provide a performance comparison between the polynomial classifier and Dynamic Time Warping (DTW). The polynomial classifier is found to outperform DTW in many aspects such as recognition rate, and computational and memory requirements.

Volume

4

First Page

3077

Last Page

3081

Disciplines

Computer Sciences

Keywords

Dynamic Time Warping, Polynomial Classifiers, Speech Recognition

Scopus ID

10944225960

Indexed in Scopus

yes

Open Access

no

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