Spoken Language Processing: A Guide to Theory, Algorithm and System Development

Remarkable progress is being made in spoken language processing, but many powerful techniques have remained hidden in conference proceedings and academic papers, inaccessible to most practitioners. In this book, the leaders of the Speech Technology Group at Microsoft Research share these advances -- presenting not just the latest theory, but practical techniques for building commercially viable products.KEY TOPICS:Spoken Language Processing draws upon the latest advances and techniques from multiple fields: acoustics, phonology, phonetics, linguistics, semantics, pragmatics, computer science, electrical engineering, mathematics, syntax, psychology, and beyond. The book begins by presenting essential background on speech production and perception, probability and information theory, and pattern recognition. The authors demonstrate how to extract useful information from the speech signal; then present a variety of contemporary speech recognition techniques, including hidden Markov models, acoustic and language modeling, and techniques for improving resistance to environmental noise. Coverage includes decoders, search algorithms, large vocabulary speech recognition techniques, text-to-speech, spoken language dialog management, user interfaces, and interaction with non-speech interface modalities. The authors also present detailed case studies based on Microsoft's advanced prototypes, including the Whisper speech recognizer, Whistler text-to-speech system, and MiPad handheld computer.MARKET:For anyone involved with planning, designing, building, or purchasing spoken language technology.

XUEDONG HUANG is founder and head of the Speech Technology Group at Microsoft Research. He received his Ph.D. from the University of Edinburgh. He is an IEEE Fellow.

ALEX ACERO and HSIAO-WUEN HON are Senior Researchers at Microsoft Research and Senior Members of IEEE. Both received doctorates from Carnegie Mellon University.

Foreword by Dr. Raj Reddy, Carnegie Mellon University