Speech and language processing
by Dan Jurafsky, Daniel Jurafsky, James H. Martin · first published 2000
91% recommend9% neutral
Why HN recommends it
Standard NLP textbook with a clear, well-paced introduction to the field, from regular expressions and n-gram language models to embeddings and transformers. Suits newcomers and self-learners; free draft online.
Summarised by Claude from recommending comments
"This book offers a unified vision of speech and language processing, presenting state-of-the-art algorithms and techniques for both speech and text-based processing of natural language. This comprehensive work covers both statistical and symbolic approaches to language processing; it shows how they can be applied to important tasks such as speech recognition, spelling and grammar correction, information extraction, search engines, machine translation, and the creation of spoken-language dialog agents."--BOOK JACKET.
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Managing Gigabytes (Witten) Information Retrieval (Manning) Text Compression (Bell) Natural Language Processing (Manning) Natural Language Understanding (Allen) Speech and Language Processing (Jurafsky) The Text Mining Handbook (Sanger) Statistical Machine Translation (Koehn) Data-Intensive Text Processing with MapReduce (Lin) Algorithms on strings (Gusfield) Jewels of Stringology (Crochemore)…
on “Ask HN: Best Text Mining Resources” ↗These two books are really recommended: - Speech and Language Processing, Jurafsky and Martin - Foundations of Statistical Natural Language Processing, Chris Manning and Hinrich Schütze Together they provide a very good overview of the field, from tokenization to robust…
on “Natural language processing in Clojure, Go ,Cython” ↗Speech and Language Processing by Jurafsky and Martin Foundations of Statistical Natural Language Processing by Manning and Schütze I have to say comments like yours are not really encouraging to continue writing ;).
on “Natural Language Processing for the Working Programmer” ↗…A Probabilistic Perspective" by Murphy. For more depth on graphical models look at "Probabilistic Graphical Models: Principles and Techniques" by Koller. On the NLP front there's the standard texts "Speech and Language Processing" by Jurafsky and "Foundations of Statistical Natural Language Processing" by Manning. I also like "An Introduction to Statistical Learning" by James, Witten, Hastie and Tibshirani.
on “Level-Up Your Machine Learning” ↗…Predictive modelling cover a lot of the classical techniques. For univariate time series forecasting "Forecasting Principles and Practice" is great. For natural language processing foundations Jurafsky's Speech and Language Processing is broadly recommended; for cutting edge natural language processing Stanford's CS224n is great: http://web.stanford.edu/class/cs224n/
on “Ask HN: Full-on machine learning for 2020, what are the best resources?” ↗There are a ton of different ways to approach the problem of interpreting a command. if you're interested in a solid reference for computational linguistics, then i recommend either 'speech and language processing' by jurafsky et al or the 'oxford handbook of computational linguistics'. finally, the forthcoming information retrieval book (http://www-csli.stanford.edu/~hinrich/information-retrieval-...) is a fantastic…
on “Wundrbar is the next generation of search (YC Winter 08)” ↗…(http://www.paulgraham.com/spam.html and http://www.paulgraham.com/better.html). They're probably a decent high-level introduction to the area. For a more in-depth, yet very accessible discussion, I would recommend "Speech and Language Processing" by Jurafsky & Martin (http://books.google.com/books/about/SPEECH_AND_LANGUAGE_PROC...). It's considered by many to be the Bible of NLP.
on “Generating random text” ↗…relatively new to the material (like me). That said, if you take a look at the link to the course, the professors recommend a few different texts: "The best textbook for the class is Jurafsky and Martin, Speech and Language Processing 2nd Edition (http://www.cs.colorado.edu/~martin/slp.html), complemented by chapters from Manning, Schütze and Raghavan 2008 (http://nlp.stanford.edu/IR-book/); other useful, good books include Manning…
on “Peter Norvig review of "Foundations of Statistical NLP"” ↗I think the book "Speech and Language Processing, 2nd Edition" from Prof. Daniel Jurafsky is very good http://www.amazon.com/Speech-Language-Processing-Daniel-Jura... You can also check out the great online NLP course taught by the author and Prof.…
on “Parsing English with 500 lines of Python (2013)” ↗…"Foundations of Statistical Natural Language Processing" by Manning and Schuetze is of significantly higher quality, and explains many of the concepts you will need for information retrieval. Also, "Speech and Language Processing" by Jurafsky and Martin is an excellent book.
on “Introduction to Information Retrieval” ↗If people don't want to learn it, it won't happen. With that being said, I found the introduction to regular expressions in Speech and Language Processing, by Daniel Jurafsky to be the only one where it clicked for me what was going on.
on “Understanding Regular Expressions 2: Groups and Captures” ↗…natural language processing. Instead, I did a simple project on searching using language processing and just read Foundations of Statistical Natural Language Processing [1], which is not too difficult, and Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics and Speech Recognition [2], which is a pretty heavy read but a great reference. I was able to find a used copy of the second…
on “CS224d: Deep Learning for Natural Language Processing” ↗For pure linguistics I'd recommend Transformational Grammar by Andrew Radford and Metaphors We Live By by George Lakoff and Mark Johnson. And for NLP, Dan Jurafski and James H. Martin's Speech and Language Processing is excellent, and there are great projects like spaCy, NLTK, WordNet, FrameNet, COCA. etc.
on “Ask HN: What single book is the best intro to your field for laypeople?” ↗…Minimum: What You Need to Know to Start Doing Physics" by Leonard Susskind. I'm reading the entire series and it's very clear and interesting, definitely recommend if you want to get into physics. - "Speech and Language Processing (3rd ed. draft)" - Really good intro to natural language processing. - Kar by Orhan Pamuk - not a technical book just an intriguing fiction book in turkish I want to read to work on my Turkish;.
on “Ask HN: Technical Summer Reading List” ↗…Loper, is a great intro to NLP concepts and working with NLTK which maybe a bit dated to some but it would definitely recommend, and its online for free. Great examples.(https://www.nltk.org/book/) - Speech and Language Processing - Dan Jurafsky and James H. Martin - is good, though I have only spent much time with the pre-print And then theres a lot of papers that are good reads. Let me know if you have any questions or want…
on “Ask HN: What are the foundational texts for learning about AI/ML/NN?” ↗