This book offers a state-of-the-art survey of methods and techniques for structuring, acquiring and maintaining lexical resources for speech and language processing. The first chapter provides a broad survey of the field of computational lexicography, introducing most of the issues, terms and topics which are addressed in more detail in the rest of the book. The next two chapters focus on the structure and the content of man-made lexicons, concentrating respectively on (morpho-)syntactic and (morpho-)phonological information. Both chapters adopt a declarative constraint-based methodology and pay ample attention to the various ways in which lexical generalizations can be formalized and exploited to enhance the consistency and to reduce the redundancy of lexicons. A complementary perspective is offered in the next two chapters, which present techniques for automatically deriving lexical resources from text corpora. These chapters adopt an inductive data-oriented methodology and focus also on methods for tokenization, lemmatization and shallow parsing. The next three chapters focus on speech applications, more specifically on the organization of speech data bases, and on the use of lexica in speech synthesis and speech recognition. The last chapter takes a psycholinguistic perspective and addresses the relation between storage and computation in the mental lexicon. The relevance of these topics for speech and language processing is obvious, for since NLP systems need large lexica in order to achieve reasonable coverage, and since the construction and maintenance of large-size lexical resources is a complex and costly task, it is of crucial importance for those who design or build such systems to be aware of the latest developments in this fast-moving field. The intended audience for this book includes advanced students and professional scientists working in the areas of computational linguistics and language and speech technology.
A unique overview of the human language faculty at all levels of organization. Language is not only one of the most complex cognitive functions that we command, it is also the aspect of the mind that makes us uniquely human. Research suggests that the human brain exhibits a language readiness not found in the brains of other species. This volume brings together contributions from a range of fields to examine humans' language capacity from multiple perspectives, analyzing it at genetic, neurobiological, psychological, and linguistic levels. In recent decades, advances in computational modeling, neuroimaging, and genetic sequencing have made possible new approaches to the study of language, and the contributors draw on these developments. The book examines cognitive architectures, investigating the functional organization of the major language skills; learning and development trajectories, summarizing the current understanding of the steps and neurocognitive mechanisms in language processing; evolutionary and other preconditions for communication by means of natural language; computational tools for modeling language; cognitive neuroscientific methods that allow observations of the human brain in action, including fMRI, EEG/MEG, and others; the neural infrastructure of language capacity; the genome's role in building and maintaining the language-ready brain; and insights from studying such language-relevant behaviors in nonhuman animals as birdsong and primate vocalization. Section editors Christian F. Beckmann, Carel ten Cate, Simon E. Fisher, Peter Hagoort, Evan Kidd, Stephen C. Levinson, James M. McQueen, Antje S. Meyer, David Poeppel, Caroline F. Rowland, Constance Scharff, Ivan Toni, Willem Zuidema
An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition
Author: Dan Jurafsky
Publisher: Prentice Hall
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.
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.
Auditory processing in children (APD) comprises an increasingly important clinical area within the broad field of communication disorders. This new textbook presents the major advances in the assessment and management of APD. The chapter authors, highly regarded clinicians and researchers from diverse professional groups, contribute an impressive breadth of knowledge to explain and demystify APD. This text will be useful to students of speech language pathology and audiology, as well as professionals in those fields.
A Guide to Theory, Algorithm, and System Development
Author: Xuedong Huang
Publisher: Prentice Hall
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.
Master modern web and network data modeling: both theory and applications. In Web and Network Data Science, a top faculty member of Northwestern University’s prestigious analytics program presents the first fully-integrated treatment of both the business and academic elements of web and network modeling for predictive analytics. Some books in this field focus either entirely on business issues (e.g., Google Analytics and SEO); others are strictly academic (covering topics such as sociology, complexity theory, ecology, applied physics, and economics). This text gives today's managers and students what they really need: integrated coverage of concepts, principles, and theory in the context of real-world applications. Building on his pioneering Web Analytics course at Northwestern University, Thomas W. Miller covers usability testing, Web site performance, usage analysis, social media platforms, search engine optimization (SEO), and many other topics. He balances this practical coverage with accessible and up-to-date introductions to both social network analysis and network science, demonstrating how these disciplines can be used to solve real business problems.
Without sacrificing coverage of such important fundamental concepts as history, ethics, information systems and systems analysis, this introductory textbook features detailed coverage of recent technological advances in hardware - image scanners, laptop computer displays, reduced instruction set computers, fascimile machines, robotics and factory automation, CIM, the