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- W2396062212 abstract "Models for computer recognition of continuous speech generally fall into one of two types: network models and multiple knowledge source models. The objective of this research is to develop a network model of continuous speech recognition which allows multiple knowledge sources to participate in the recognition process. The vehicle for accomplishing this research is the Puff system for continuous speech recognition.The Puff system was implemented with two real knowledge sources (phonemic and unvoiced/voiced/silence) and two simulated knowledge sources (word and semantic). The recognition task selected was a voice entry desk calculator. The experimental results are analyzed and compared with results for other systems performing similar tasks.Puff as a system offers significant advantages over other continuous speech recognition systems. The search space reduction paradigm, the hierarchical knowledge networks and the scoreboard mechanism differentiate Puff from other systems. It is as accurate as the best of its predecessor systems, has multiple knowledge source flexibility, is written in a common high level language, and provides an effective environment for experimentation in speech recognition." @default.
- W2396062212 created "2016-06-24" @default.
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- W2396062212 date "1982-01-01" @default.
- W2396062212 modified "2023-09-27" @default.
- W2396062212 title "The puff speech recognition system" @default.
- W2396062212 hasPublicationYear "1982" @default.
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