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Robust Gender Identification using EMD-Based Cepstral Features
2018
Asia-Pacific Journal of Information Technology and Multimedia
Automatic speaker gender identification is a field of research with numerous practical applications. However, this issue has not gained its deserved attention, in particular in the presence of environmental noises. In this paper, using the empirical mode decomposition (EMD), some new and improved mel-frequency cepstral coefficient (MFCC) features are developed to address the problem of robust speaker gender identification. In the proposed approach, EMD is employed as a filter bank to decompose
doi:10.17576/apjitm-2018-0701-06
fatcat:ehh35ys7xbarzk4xdogfvbyh7i