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Parameter Settings for Speaker Identification using Gaussian Mixture Model

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2 Author(s)
Eskidere, O. ; Uludag Univ. Teknik Bilimler MYO, Bursa, Turkey ; Ertas, F.

In this paper, the impact of the number of Gaussian mixtures, the duration of training and testing sessions, and the number of speakers on speaker identification has been investigated using clean speech (TIMIT) and telephone speech (NTIMIT) databases. Employing the parameters that provide the maximum performance, 100% and 85.71% identification rates have been obtained for the TIMIT and NTIMIT databases, respectively.

Published in:

Signal Processing and Communications Applications, 2007. SIU 2007. IEEE 15th

Date of Conference:

11-13 June 2007