In this paper we describe the design of a phoneme classifier that is based on AIDA, a speech database that has been recently proposed as a standard for Italian concerning the phonetic level. We present experimental results using LVQ and show that the proper selection of Kohonen's learning parameter alpha, based on some intriguing links with Backpropagation learning, contributes to improve the performance with respect to standard heuristics proposed in the literature [Konen, Proc. IEEE 78 (9) (1990) 1464-1480], (C) 2000 Published by Elsevier Science B.V. All rights reserved.
Cosi, P., Frasconi, P., Gori, M., Lastrucci, L., Soda, G. (2000). Competitive radial basis functions training for phone classification. NEUROCOMPUTING, 34(1-4), 117-129 [10.1016/S0925-2312(00)00312-X].
Competitive radial basis functions training for phone classification
Gori M.;
2000-01-01
Abstract
In this paper we describe the design of a phoneme classifier that is based on AIDA, a speech database that has been recently proposed as a standard for Italian concerning the phonetic level. We present experimental results using LVQ and show that the proper selection of Kohonen's learning parameter alpha, based on some intriguing links with Backpropagation learning, contributes to improve the performance with respect to standard heuristics proposed in the literature [Konen, Proc. IEEE 78 (9) (1990) 1464-1480], (C) 2000 Published by Elsevier Science B.V. All rights reserved.
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https://hdl.handle.net/11365/36520
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