Abstract
A text-dependent speaker recognition system base on Radial Basis Function (RBF) neural network is presented. A two-stage recognition approach is proposed, in which the speaker-cohort model and the gender model are integrated to give the decision. The speaker recognition system has been evaluated in terms of both speaker verification and closed-set speaker identification. The results clearly indicate that the two-stage procedure is able to improve the overall performance of the speaker recognition system.
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© 2002 Springer-Verlag Berlin Heidelberg
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Jianping, D., Venkateswarlu, R. (2002). Speaker Recognition Using Radial Basis Function Neural Networks. In: Abraham, A., Köppen, M. (eds) Hybrid Information Systems. Advances in Soft Computing, vol 14. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-1782-9_6
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DOI: https://doi.org/10.1007/978-3-7908-1782-9_6
Publisher Name: Physica, Heidelberg
Print ISBN: 978-3-7908-1480-4
Online ISBN: 978-3-7908-1782-9
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