Rahimi Azghadi, S. Mostafa, Bonyadi, M. Reza, and Shah-Hosseini, Hamed (2007) Gender classification based on feedforward backpropagation neural network. In: Proceedings of the 4th IFIP International Conference on Artificial Intelligence Applications and Innovations. pp. 299-304. From: AIAI 2007: 4th IFIP International Conference on Artificial Intelligence Applications and Innovations, 19-21 September 2007, Athens, Greece.

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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.

Item ID:	45701
Item Type:	Conference Item (Research - E1)
ISSN:	1868-4238
Date Deposited:	09 Aug 2017 00:57
FoR Codes:	08 INFORMATION AND COMPUTING SCIENCES > 0801 Artificial Intelligence and Image Processing > 080108 Neural, Evolutionary and Fuzzy Computation @ 100%
SEO Codes:	97 EXPANDING KNOWLEDGE > 970109 Expanding Knowledge in Engineering @ 100%
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