- Paperback: 1008 pages
- Publisher: Prentice Hall; 1 edition (May 5, 2001)
- Language: English
- ISBN-10: 0130226165
- ISBN-13: 978-0130226167
- Product Dimensions: 7 x 2 x 9.1 inches
- Shipping Weight: 3.2 pounds (View shipping rates and policies)
- Average Customer Review: 13 customer reviews
Amazon Best Sellers Rank:
#1,265,681 in Books (See Top 100 in Books)
- #139 in Books > Computers & Technology > Computer Science > AI & Machine Learning > Natural Language Processing
- #163 in Books > Engineering & Transportation > Engineering > Telecommunications & Sensors > Signal Processing
- #445 in Books > Engineering & Transportation > Engineering > Civil & Environmental > Acoustics
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Spoken Language Processing: A Guide to Theory, Algorithm and System Development 1st Edition
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From the Inside Flap
Our primary motivation in writing this book is to share our working experience to bridge the gap between the knowledge of industry gurus and newcomers to the spoken language processing community. Many powerful techniques hide in conference proceedings and academic papers for years before becoming widely recognized by the research community or the industry. We spent many years pursuing spoken language technology research at Carnegie Mellon University before we started spoken language R&D at Microsoft. We fully understand that it is by no means a small undertaking to transfer a state-of-the-art spoken language research system into a commercially viable product that can truly help people improve their productivity. Our experience in both industry and academia is reflected in the context of this book, which presents a contemporary and comprehensive description of both theoretic and practical issues in spoken language processing. This book is intended for people of diverse academic and practical backgrounds. Speech scientists, computer scientists, linguists, engineers, physicists, and psychologists all have a unique perspective on spoken language processing. This book will be useful to all of these special interest groups.
Spoken language processing is a diverse subject that relies on knowledge of many levels, including acoustics, phonology, phonetics, linguistics, semantics, pragmatics, and discourse. The diverse nature of spoken language processing requires knowledge in computer science, electrical engineering, mathematics, syntax, and psychology. There are a number of excellent books on the subfields of spoken language processing, including speech recognition, text-to-speech conversion, and spoken language understanding, but there is no single book that covers both theoretical and practical aspects of these subfields and spoken language interface design. We devote many chapters systematically introducing fundamental theories needed to understand how speech recognition, text-to-speech synthesis, and spoken language understanding work. Even more important is the fact that the book highlights what works well in practice, which is invaluable if you want to build a practical speech recognizer, a practical text-to-speech synthesizer, or a practical spoken language system. Using numerous real examples in developing Microsoft's spoken language systems, we concentrate on showing how the fundamental theories can be applied to solve real problems in spoken language processing.
From the Back Cover
- New advances in spoken language processing: theory and practice
- In-depth coverage of speech processing, speech recognition, speech synthesis, spoken language understanding, and speech interface design
- Many case studies from state-of-the-art systems, including examples from Microsoft's advanced research labs
Spoken Language Processing draws on the latest advances and techniques from multiple fields: computer science, electrical engineering, acoustics, linguistics, mathematics, psychology, and beyond. Starting with the fundamentals, it presents all this and more:
- Essential background on speech production and perception, probability and information theory, and pattern recognition
- Extracting information from the speech signal: useful representations and practical compression solutions
- Modern speech recognition techniques: hidden Markov models, acoustic and language modeling, improving resistance to environmental noises, search algorithms, and large vocabulary speech recognition
- Text-to-speech: analyzing documents, pitch and duration controls; trainable synthesis, and more
- Spoken language understanding: dialog management, spoken language applications, and multimodal interfaces
To illustrate the book's methods, the authors present detailed case studies based on state-of-the-art systems, including Microsoft's Whisper speech recognizer, Whistler text-to-speech system, Dr. Who dialog system, and the MiPad handheld device. Whether you're planning, designing, building, or purchasing spoken language technology, this is the state of the artfrom algorithms through business productivity.
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The first two sections cover the fundamental theories that should be understood before embarking in-depth into a study of speech processing. This may seem an obvious approach but many texts do not follow this pattern making their use as reference tomes limited. Separating background theory from its use is also useful in that it allows a rigorous approach to its description. Too often texts give a hurried imprecise overview of theories used before launching into a long and complex use of the theory; losing the reader instantly in a quagmire of formulae.
The first two sections of the book deals with background material, material that the reader should at least understand the key concepts of. The first section concentrates on speech in general (including production and perception), probability and statistics, and pattern classification. These last two topics mentioned are both important parts of the book and are dealt with in their own chapters. Both are well written with the right amount of explanation and background. Much of the remainder of the book expects at least some familiarity with the material presented here. These chapters, like all chapters in the book finish with a section entitled, "Historical Perspective and Further Reading". The inclusion of recommended further reading, in addition to the vast number of references appearing in each chapter, make the book as a whole a very good starting point for any work in speech processing.
The second section concerns itself with the DSP topics which relate to speech processing. In this section the reader will find everything from FFTs to multi-rate signal processing and speech signal representations to speech coding. Again the section is well written and the reader is not forced to refer to other texts to understand what is written. If a topic is not expanded upon here then it is an indication that is not dealt further in any great depth in the remainder of the book.
The third section of the book covers speech recognition and is probably the section which will find most use with many readers. This section is very thorough in its treatment of the subject. It starts immediately with a discussion of Hidden Markov Models which is almost exclusively the method employed in the pattern matching stage of speech recognition. Any algorithms that are mentioned are also detailed which really make the book useful. In fact algorithms are presented throughout the book making it a practical reference as much as a theoretical one. This is important because there is a big jump from understanding theory to being able to implement an algorithm to exploit that theory. Other topics covered include an excellent chapter on environmental robustness with one of the best discussions of microphones I have seen. Language modelling and search algorithms are given a thorough treatment. I would like to have seen more detailed information on front-end processing and endpoint detection, as this remains a critical stage of the recognition process. Perhaps the level of detail reflects the fact that this is currently a hot research topic with potential for significant advancement.
Section four, on text-to-speech processing, is a good overview of the field and better than any book I've seen on the subject. It shows numerous block diagrams of what you need to build such a system and gives numerous algorithms in pseudocode. It also dedicates a subsection to each block of the text-to-speech system block diagram, discussing in detail what you would need to do to implement that particular block. Since much of the individual blocks have been discussed earlier in the book, it refers you back to specific earlier sections for details.
The fifth section is a short one on entire systems and shows some case studies, concentrating on what Microsoft was doing at the time this book was published, since that is where the authors' research came from. I would highly recommend that anyone anticipating getting into speech processing have a copy of this classic nearby.
For newcomers to the field I would recommend starting with Jurafsky & Martin's excellent "Speech and Language Processing" instead. That book covers NLP as well, so it is more superficial, but it does a much better job of explaining the basics. If you need more detail on speech technology than that provides you, then consider this one.
For details, you might also want to have a look at "The Springer Handbook of Speech Processing", preferably at a library. And Holmes and Holmes's "Speech Synthesis and Recognition" gives a very good non-technical account of the speech technology field.
many algorithms described in this book have been rigorously tested either by the authors or by their close co-workers. They are not a random set of algorithms. Rather, they are very effective and useful in practice.
Errata: p.38 "ax" schwa sound is FIRST syllable of "ago", not second. High/(neutral)/low and front/(neutral)/back cannot be four binary systems, because it's impossible to have a [+high, +low] or a [+front, +back] vowel. They are two trinary systems. You can represent them by four binary systems if you want to pervert the notation, but you should not call them that.