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Abstract

A method and apparatus for estimating parameters of a new hidden Markov model (HMM) applicable to pattern recognition such as recognition of speech signals which are time series signals, and a method and apparatus for pattern recognition employing this HMM. It is easily applicable to speech and other time series signals. In particular, the pattern recognition degree of a time series observation vector signal y, received from an information source, is calculated by using function values u(y,1), u(y,2), . . . , u(y,M) and occurrence probabilities of signals C.sub.1, C.sub.2, . . . , C.sub.M which are composed of set C, where u(y,m) is the image into which the pair (C.sub.m,Y) is mapped, u(y,m).epsilon.U (U=[a,b], a,b.epsilon.R.sup.1 and 0.ltoreq.a.ltoreq.b) and y.epsilon.R.sup.n (R.sup.n :n-dimensional Euclidean space). C is a set of signals against which the observation vector signal y is compared.

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