Abstract
A method has been developed for increasing the computational efficiency in spoken word recognition based on template matching using dynamic programming (DP matching). It is based on the detection and utilization of points along the time axis where the acoustic features of the speech signal are quasistationary. These quasi-stationary points (QS-points) are determined both for the input speech and for the stored templates, and are used for (1) pre-selection of candidate templates for DP matching, and (2) reduction of the search space for piecewise DP matching between corresponding intervals of the input signal and a candidate template. A recognition experiment on a 50-word vocabulary indicates that the method can reduce the computation time to 36% of the time required for a conventional DP matching method. >
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