Overview

Voice or speech recognition is the ability of a machine or program to receive and interpret dictation, or to understand and carry out spoken commands. The task of speech recognition is to convert speech into a sequence of words by a computer program. As the most natural communication modality for humans, the ultimate dream of speech recognition is to enable people to communicate more naturally and effectively. Speech recognition is often regarded as the front-end for many NLP components discussed in this book. In practice, the speech system typically uses context-free grammar (CFG) or statistic n-grams for the same reason that hidden Markov models (HMMs) are used for acoustic modelling. Although it initially addressed applications requiring the scanning of audio data for occurrences of particular keywords, the technology has become an effective approach to speech recognition for a wide range of applications. Speech recognition applications are different from any other kind of computer application. It opens up a world of possibilities for developers, especially those building interactive voice responses (IVRs) and other telephony applications, but speech recognition also has some challenges. Speech recognition is also affected by the quality of the input. If a user is calling a system, a bad cell phone connection or overly compressed Internet audio may throw off recognition. Handling these sorts of cases becomes very important when designing speech recognition applications. Modern Speech Recognition Approaches reflect important research on the approaches of speech recognition. The book focuses primarily on speech recognition and the related tasks such as speech enhancement and modelling. Thorough reading of this book will provide comprehensive knowledge on modern speech recognition approaches to the readers.

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9781681174617

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