Abstract
This chapter describes some highlights of the recent developments in digital pattern recognition. The topics included provide primarily an update from the first edition of the book. First, a general framework for pattern recognition is proposed. The interpretations of the three major approaches, namely, template-matching, decision-theoretic, and syntactic, in terms of the same general framework are given. Tree grammars, stochastic languages, error-correcting parsing and clustering for syntactic pattern recognition are then briefly described. Finally, recent results in picture and speech recognition such as detection and extraction of objects, representation of objects and pictures and ARPA speech understanding project are summarized.KeywordsSpeech RecognitionMinimum Span TreeSpeech Recognition SystemTree AutomatonInput SentenceThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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