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Neural networks for improved text-independent speaker identification

Yue, Xicai; Ye, Datian; Zheng, Changxun; Wu, Xiaoyu

Authors

Alex Yue Alex.Yue@uwe.ac.uk
Senior Lecturer in Bioinstrumentation and Sensor Interfacing

Datian Ye

Changxun Zheng

Xiaoyu Wu



Abstract

In this article, we consider the binary partitioned approach with pattern index information, propose an neural network array (NNA) that performs the pattern recognition task by combining the binary partitioned approach with decision trees, and verify that the NNA can not only reduce the computation cost of training and recognition but also reduce the classification error rate. Speaker identification with the radial basis function neural network array (RBFNNA) is discussed in detail as an application of the NNA.

Citation

Yue, X., Ye, D., Zheng, C., & Wu, X. (2002). Neural networks for improved text-independent speaker identification. IEEE Engineering in Medicine and Biology Magazine, 21(2), 53-58. https://doi.org/10.1109/MEMB.2002.1000186

Journal Article Type Article
Publication Date 2002-04
Deposit Date May 7, 2021
Journal IEEE Engineering in Medicine and Biology Magazine
Print ISSN 0739-5175
Peer Reviewed Peer Reviewed
Volume 21
Issue 2
Pages 53-58
DOI https://doi.org/10.1109/MEMB.2002.1000186
Public URL https://uwe-repository.worktribe.com/output/5667478