Speech Recognition and Understanding

Alex Acero

Abstract: Speech is man’s most natural channel of communication, so it is only natural that it should be the subject of much work in pattern recognition. Recognizing speech is difficult, for the nature of the speech communication process is such that the resulting acoustic signal is highly encoded and full of contextual dependencies. Speech perception on the part of a human listener requires him to utilize his linguistic knowledge to undo the encoding. Machines that aspire to recognize the same signal must be able to apply similar constraints. Current work in automatic speech recognition ranges from systems that recognize isolated words from limited vocabularies to systems that “understand” the meaning of naturally spoken sentences, using higher level linguistic constraints in addition to the information derived from the speech signal itself. This chapter describes the techniques developed and the progress made in speech recognition and understanding in the early 1970’s.