Abstract
This paper deals with a method of speech recognition using dynamic programming (DP) matching and LVQ techniques. It is well known that learning vector quantization (LVQ) can generate some good reference vectors from many vectors and its algorithm is very simple. On the other hand, the DP matching method has good performance for the recognition of continuous speech. However, in general, this method requires many reference vectors. In this paper, we present a new method of speech recognition using both LVQ clustering and DP matching.
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