Abstract
An efficient reduced RBF networks array for speaker recognition is proposed in this paper. The reduced method combines the advantages of IOC and ROLS algorithms. Not only the number but also the positions of data centers are adapted in training progress, which optimizes the structure of network very well. Moreover, the experiments on a closed set, text-independent speaker recognition system show that, better robustness and simpler networks can be achieved through this improved algorithm in comparison with classical RBFN.
This research is supported by the National Science Foundation (NSF 60171036, 30370392), China.
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Lian, H., Wang, Z., Wang, J., Zhang, L. (2004). Speaker Identification Using Reduced RBF Networks Array. In: Yin, FL., Wang, J., Guo, C. (eds) Advances in Neural Networks – ISNN 2004. ISNN 2004. Lecture Notes in Computer Science, vol 3173. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-28647-9_152
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DOI: https://doi.org/10.1007/978-3-540-28647-9_152
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