An explosion of Web-based language techniques, merging of distinct fields, availability of phone-based dialogue systems, and much more make this an exciting time in speech and language processing. The first of its kind to thoroughly cover language technology – at all levels and with all modern technologies – this book takes an empirical approach to the subject, based on applying statistical and other machine-learning algorithms to large corporations. Builds each chapter around one or more worked examples demonstrating the main idea of the chapter, usingthe examples to illustrate the relative strengths and weaknesses of various approaches. Adds coverage of statistical sequence labeling, information extraction, question answering and summarization, advanced topics in speech recognition, speech synthesis. Revises coverage of language modeling, formal grammars, statistical parsing, machine translation, and dialog processing. A useful reference for professionals in any of the areas of speech and language processing.
Representing speech signals such that specific characteristics of speech are included is essential in many Air Force and DoD signal processing applications.
Designed for beginning users of Dragon Naturally Speaking, this self-paced, self-instructional guide provides the user with all the instruction necessary to become proficient in the use of this popular speech recognition software.
This book is a comprehensive and authoritative guide to voice user interface (VUI) design.
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Speech Recognition: The Complete Practical Reference Guide
The Application of Hidden Markov Models in Speech Recognition presents the core architecture of a HMM-based LVCSR system and proceeds to describe the various refinements which are needed to achieve state-of-the-art performance.
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This book presents a systematic approach to the automatic recognition of simultaneous speech signals using computational auditory scene analysis.
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