Abstract
This is an overview of techniques which have been developed for automatic pattern recognition, with an indication of their relevance to automatic speech recognition. The first part is concerned with data transformations, distance measures, cluster analysis and other aspects of what could be called ‘classic’ mathematical pattern recognition. The second part is more directly concerned with speech, and the term ‘pattern recognition’ is used to denote an approach to speech recognition which tries to avoid the problems of using a phoneme level of description and treats larger units such as words as patterns with a time axis.
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