Introduction to Computational Linguistics

Reading and Resources

NLTK

The course will use the Natural Language Toolkit (NLTK-Lite), developed at Univ of Pennsylvania by Steven Bird and Edward Loper as an open source project at Sourceforge. This year, we will be using Version 0.6 of the toolkit. NLTK-Lite is provided as a Python package and modules from the package can therefore be imported into Python programs. For more details, including documentation, see the

• NLTK Project Page

Linguistic Corpus Resources on DICE

For general information about language and speech data on DICE, have a look at the corpora web page.

A variety of corpora are also included as part of the NLTK-Lite distribution, and can be found /usr/share/nltk-data.

Recommended textbook

Daniel Jurafsky and James H. Martin. Speech and Language Processing. Prentice-Hall, 2000. (Errata)

New and revised chapters available online! Speech and Language Processing, 2nd Ed.

Python Resources

The following books and other resources are not required, but may prove useful as references for the programming portions of the course.

• How to Think Like a Computer Scientist: Learning with Python, by Allen B. Downey, Jeffrey Elkner and Chris Meyers.
  This text has been released under the Open Book Project.
• Learning Python, by Mark Lutz and David Ascher.
  This is a good book for beginners to Python. Look here for corrections, source code, etc.
• Programming Python, by Mark Lutz.
  A programmer's reference. 1255pp, and not intended for beginners.
• Dive into Python, by Mark Pilgrim.
  Advertised as a free book for "experienced programmers". The Homepage also has a number of useful links to Python resources.
• Main site for Python documentation
  Note the reference page for regular experssion syntax.
• Python FAQ (Frequently-Asked Questions list)
• Python HOWTO Page (including the Regular Expression HOWTO)

Other reading

• Chris Manning and Hinrich Schutze, Foundations of Statistical Natural Language Processing
  Full text on MIT Cognet
• Oxford Handbook of Computational Linguistics edited by Ruslan Mitkov.
• James Allen, Natural Language Understanding
• Ricardo Baeza-Yates, Berthier Ribeiro-Neto, Modern Information Retrieval
• Barbara Partee, Alice Ter Meulen, and Robert Wall, Mathematical Methods in Linguistics
• David Crystal, A Dictionary of Linguistics and Phonetics
• Steven Abney. "Statistical Methods and Linguistics." In: Judith Klavans and Philip Resnik (eds.), The Balancing Act: Combining Symbolic and Statistical Approaches to Language. The MIT Press, Cambridge, MA. 1996.