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Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics and Speech Recognition
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Author: Daniel Jurafsky, James H. Martin
List Price: $82.00
Our Price: Click to see the latest and low price
ISBN: 0130950696
Publisher: Prentice Hall (26 January, 2000)
Edition: Hardcover
Sales Rank: 73,079
Average Customer Rating: 4.33 out of 5
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Customer ReviewsRating: 5 out of 5
I looked for
something which I can use - I am a linguist - and found it immensly readable and useful
Rating: 4 out of 5
The a good introduction to NLP, but could be improved
This book helped me accomplish what I set out to do; namely to obtain an overview of the field of natural language processing, with an emphasis on language understanding (as opposed to recognition). And I can recommend it on that level. The weakness of the book however is that it left me asking, "OK, now what?". The book started off strong with a number of dynamic-programming algorithms, finite automaton models, and N-grams that one could sink his/her teeth into from an algorithmic point-of-view. But when it came to actual techniques for natural-language understanding (chapters 14-17) the goods were not delivered. The algorithms disappeared, and the best I could find was in Chapter 15 an incomplete, and unconvincing treatment of Hiyan Alshawi's semantic parsing techniques which fueled the Core Language Engine last decade. Chapter 16 dealt with lexical semantics and was almost entirely devoid of algorithms. My gut feeling after reading this text is that parsing techniques will likely give way to statistical and probabilistic learning methods that will in some sense bypass the need to correctly or accurately parse language. I cannot fault the authors for not exploring this in more depth,as this represents the cutting edge for both NLP and artificial intelligence. In any case, I'm off to read Schutze and Manning's book which will hopefully provide a bit more focus on that perspective. What intrigues me is that most people can understand some language, but very few people understand the grammar of their own language, especially if they have been deprived of a formal education. So why should computers need to know all about grammar rules and parsing? Could they instead be trained by simply being exposed to enough interactions between language and objects? I teach in a department dominated by both foreign and immigrant students. I understand them most of the time, but I would estimate that half the time their sentences or utterances would not fail to be parsed correctly.
Rating: 3 out of 5
Not bad but overrated: broad and shallow
GENERAL IDEA: Broad coverage but it lacks depth and details - particularly practical details. That is, the presentation is often too sketchy, mainly because it approaches too many subjects for its available space. I would not say that this book is strong on theory either. It is quite obvious that it avoids getting too formal and rigurous, probably to remain attractive for non-specialists too. CASE STUDY: One specific problem I had with the Hidden Markov Models, that are supperficially presented (or spread I could say) in several separate sections of the book, so it's not been a pleasure trying to actually understand them properly and completely as a fundamental concept, to make them work in my particular application. TITLE: The book's title IS misleading because it starts with "Speeech" and this book's main subject is not speech but (written) language. Actually there are only a few chapters on speech. CONCLUSION: Get this book if you are looking for a good overview of the field. As soon as you need in-depth coverage of some particular topic you will look for additional resources.
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