This major new textbook provides a clearly-written, concise and accessible introduction to speech and language processing. Assuming knowledge of only the very basics of linguistics and written specifically for students with no technical background, it is the perfect starting point for anyone beginning to study the discipline. Student s are shown from an elementary level how to use two programming languages, C and Prolog, and the accompanying CD-ROM contains all the software needed. Setting an invaluable foundation for further study, this is set to become the leading introduction to the field.

Speech and language technologies continue to grow in importance as they are used to create natural and efficient interfaces between people and machines, and to automatically transcribe, extract, analyze, and route information from high-volume streams of spoken and written information. The workshops on Mathematical Foundations of Speech Processing and Natural Language Modeling were held in the Fall of 2000 at the University of Minnesota's NSF-sponsored Institute for Mathematics and Its Applications, as part of a "Mathematics in Multimedia" year-long program. Each workshop brought together researchers in the respective technologies on the one hand, and mathematicians and statisticians on the other hand, for an intensive week of cross-fertilization. There is a long history of benefit from introducing mathematical techniques and ideas to speech and language technologies. Examples include the source-channel paradigm, hidden Markov models, decision trees, exponential models and formal languages theory. It is likely that new mathematical techniques, or novel applications of existing techniques, will once again prove pivotal for moving the field forward. This volume consists of original contributions presented by participants during the two workshops. Topics include language modeling, prosody, acoustic-phonetic modeling, and statistical methodology.

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.

Over the last 20 years, approaches to designing speech and language processing algorithms have moved from methods based on linguistics and speech science to data-driven pattern recognition techniques. These techniques have been the focus of intense, fast-moving research and have contributed to significant advances in this field. Pattern Reco

Corpus-based methods will be found at the heart of many language and speech processing systems. This book provides an in-depth introduction to these technologies through chapters describing basic statistical modeling techniques for language and speech, the use of Hidden Markov Models in continuous speech recognition, the development of dialogue systems, part-of-speech tagging and partial parsing, data-oriented parsing and n-gram language modeling. The book attempts to give both a clear overview of the main technologies used in language and speech processing, along with sufficient mathematics to understand the underlying principles. There is also an extensive bibliography to enable topics of interest to be pursued further. Overall, we believe that the book will give newcomers a solid introduction to the field and it will give existing practitioners a concise review of the principal technologies used in state-of-the-art language and speech processing systems. Corpus-Based Methods in Language and Speech Processing is an initiative of ELSNET, the European Network in Language and Speech. In its activities, ELSNET attaches great importance to the integration of language and speech, both in research and in education. The need for and the potential of this integration are well demonstrated by this publication.

Statistical approaches to processing natural language text have become dominant in recent years. This foundational text is the first comprehensive introduction to statistical natural language processing (NLP) to appear. The book contains all the theory and algorithms needed for building NLP tools. It provides broad but rigorous coverage of mathematical and linguistic foundations, as well as detailed discussion of statistical methods, allowing students and researchers to construct their own implementations. The book covers collocation finding, word sense disambiguation, probabilistic parsing, information retrieval, and other applications.