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 ?, 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].

Competitive radial basis functions training for phone classification

2000

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 ?, 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].
2000
Istituto di Scienze e Tecnologie della Cognizione - ISTC
Automatic speech recognition
Backpropagation
Competitive Radial Basis Functions
Learning Vector Quantization
Phone Classification
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/178531
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