Gender classification based on feedforward backpropagation neural network

Conference Publication ResearchOnline@JCU
Rahimi Azghadi, S. Mostafa;Bonyadi, M. Reza;Shah-Hosseini, Hamed
Mostafa Rahimi Azghadi
Abstract

Gender classification based on speech signal is an important task in variant fields such as content-based multimedia. In this paper we propose a novel and efficient method for gender classification based on neural network. In our work pitch feature of voice is used for classification between males and females. Our method is based on an MLP neural network. About 96 % of classification accuracy is obtained for 1 second speech segments.

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Publication Name

AIAI 2007: 4th IFIP International Conference on Artificial Intelligence Applications and Innovations

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ISBN/ISSN

1868-4238

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Pages Count

6

Location

Athens, Greece

Publisher

Springer

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Publisher Location

Boston, MA, USA

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DOI

10.1007/978-0-387-74161-1_32