Pattern Recognition as a Problem in Decision Theory and an Application to Speech Recognition

Abstract

After a general discussion of pattern recognition as a problem in statistical decision theory, an application of these concepts is made to the recognition of speech sounds by a method which uses the same principles for preprocessing of sound as does the human auditory system. The decision rule found for minimizing the average risk for a specified cost matrix is determined and it is shown that under appropriate conditions a pattern recognition technique which maximizes the cross correlation coefflicient of the signal with a set of functions representing the patterns is equivalent to this optimum decision rule.