Abstract

Designing a machine that mimics human behavior, particularly the capability of speaking naturally and responding properly to spoken language, has intrigued engineers and scientists for centuries. Since the 1930s, when Homer Dudley of Bell Laboratories proposed a system model for speech analysis and synthesis [1, 2], the problem of automatic speech recognition has been approached progressively, from a simple machine that responds to a small set of sounds to a sophisticated system that responds to fluently spoken natural language and takes into account the varying statistics of the language in which the speech is produced. Based on major advances in statistical modeling of speech in the 1980s, automatic speech recognition systems today find widespread application in tasks that require a human-machine interface, such as automatic call processing in the telephone network and query-based information systems that do things like provide updated travel information, stock price quotations, weather reports, etc. In this article, we review some major highlights in the research and development of automatic speech recognition during the last few decades so as to provide a technological perspective and an appreciation of the fundamental progress that has been made in this important area of information and communication technology.

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