Voice-based gender identification via multiresolution frame classification of spectro-temporal maps

Authors:
M. Abdollahi;E. Valavi;H. Ahmadi Noubari
Affiliations:
Electrical and Computer Engineering Department, University of Tehran, Tehran, Iran;Electrical and Computer Engineering Department, University of Tehran, Tehran, Iran;University of British Columbia, Vancouver, Canada and Electrical and Computer Engineering Department, University of Tehran, Tehran, Iran
Venue:
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Year:
2009

Citing 2
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Gender identification using a general audio classifier

ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 1
Computational Auditory Scene Analysis: Principles, Algorithms, and Applications

Computational Auditory Scene Analysis: Principles, Algorithms, and Applications

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Abstract

This paper presents a novel approach to gender identification based on adaptive multiresolution (MR) classification of spectro-temporal maps. The images of speech signals in this work are mainly provided by auditory inspired spectro-tem poral representations: mel-spectrogram, cochleagram and auditory spectrogram. The 2-D representation of a segment of an utterance is used as the input to the system. The system adds MR decomposition in front of a generic classifier consisting of feature extraction and classification in each MR subspace, finally combined into a global decision using a weighting algorithm. It has been shown that the accuracy of the proposed method, by rising up to 99%, significantly outperforms the accuracy of most of other common algorithms which combine pitch and acoustical features for gender identification.