Textbook and Readings
The required text is:
Daniel Jurafsky and James H. Martin. 2008. Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics and Speech Recognition. Second Edition. Prentice Hall.
- Buy it at the Stanford Bookstore or Amazon.
Of course, we're also fond of:
Christopher D. Manning and Hinrich Schütze. 1999. Foundations of Statistical Natural Language Processing. MIT Press.
- Buy it at the Stanford Bookstore or Amazon.
- You can read the text online from the Stanford network! It's referred to as M&S in the syllabus. While a bit older, it also has good and often distinct coverage of many topics. Please see http://nlp.stanford.edu/fsnlp/ for supplementary information about the text, including errata, and pointers to online resources.
Other useful reference texts for NLP are:
- Steven Bird. 2009. Natural Language Processing with Python. O'Reilly. (Free on SearchWorks)
- Philipp Koehn. 2010. Statistical Machine Translation. Cambridge.
- Yoshua Bengio. 2009. Learning Deep Architectures for AI. Technical Report. (Free from Stanford network)
- Frederick Jelinek. 1998. Statistical Methods for Speech Recognition. MIT Press.
- James Allen. 1995. Natural Language Understanding. Benjamin/Cummings, 2ed.
Other papers with relevant material will be posted on the syllabus, as will lecture slides.
