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.
Customer Reviews:
Avg. Customer Rating: 4.5 / 5.0
Big improvement over the first edition:
As its lengthy subtitle suggests, this is a big book (just under a thousand pages) and unbelievably comprehensive. On the whole, the book is a major improvement over its predecessor. The first edition was plagued with typos on seemingly every page, and was also way too thin in certain places. I seem to remember them rushing through phonetics in a single page or two, and then describing optimality theory in just a couple sentences! The second edition's coverage of the field is significantly broader and... more info
quite good, but still has improvement space:
This book is quite good if you are interested in NLP.
If the could author provide a CD with some demos,source codes and applications, it, the reader can understand the contend in this book easier.
This course is really realy difficult.
Great introductions and reference book:
I read the first edition of that book and it is terrific. The second edition is much more adapted to current research. Statistical methods in NLP are more detailed and some syntax-based approaches are presented. My specific interest is in machine translation and dialogue systems. Both chapters are extensively rewritten and much more elaborated. I believe this book is perfect for everyone who starts in speech and language processing. With precision, coherent examples and some humor, this book give a great... more info
Needs a second volume which explains the first:
This book is by now an accepted classic in the field. It is basically the only textbook that covers so much of computational linguistics, so I have had no choice but to use it for the past several years. Just the same, I'd rather not use it for teaching linguistics students. While the book has much to offer the professional, including a broad range of topics extensively researched, it is much more useful in this "handbook" capacity than as a textbook for the uninitiated. The chief reasons for this are: 1)... more info
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