Approaches to the Machine Recognition of Conversational Speech

Abstract

Publisher Summary This chapter focuses on the analysis of the problems that have to be solved to achieve machine recognition of conversational speech, and discusses some possible avenues along which the design of conversational speech-recognition systems are likely to proceed. Machine recognition of speech is the translation of the continuously varying acoustical speech signal into a sequence of discrete symbols representing linguistically defined units. The chapter discusses the reasons for interest in machine recognition of conversational speech, fundamentals of speech recognition, speech recognition as a mapping operation, speech recognition as the complement to speech production, and operational requirements for speech-recognition systems. The approaches to the recognition of conversational speech show wide ranges in three major areas: segmentation and classification, consideration of speaker variations, and information processing. Three approaches that appear to have chances for successful implementations and that have the potential of conversational speech recognition are described in continuous dynamic pattern match, phonological parametric decoding, and phonological digital decoding. Speech recognition efforts in the near future will play the role of providing instrumentation for research in phonetics, phonology, and linguistics rather than that of developing man–machine interfaces. The development of operational automatic-recognition systems for truly conversational speech appears to be a project for the far future.