Course Organization for Linguistics 889, Spring 1997

1. Goals.
   • CL Background: some familiarity with grammars, automata, parsing, algorithms
   • Non-CL Background: Computer science or programming; linguistics; cognitive science
   
   Goal: By the end of the course, everybody, regardless of background, should be familiar with the relevant basics of computational linguistics (but not all; consider taking Linguistics 645 concurrently) and understand the new trends in corpus-based and statistical methods.

2. Readings.
   • On average, 2 per week, one more fundamental, one more advanced.
   • For students with a CL background:
     • Skim the foundations paper to refresh your memory
     • Read the advanced paper carefully before class
   • For students with a non-CL background:
     • Read the foundations paper carefully before class
     • Skim the advanced paper before class
     • Get up to speed on the advanced topic in class
     • Read the advanced paper carefully after class

3. Exercises. There will be occasional exercises getting students "hands on" experience, including both on-paper and basic computational exercises, but without any serious programming. All on-line work will be done in a Unix environment.

4. Mailing list. Questions and out-of-class discussion will be handled using an electronic mailing list. Everyone is encouraged to use this list informally -- not just for official announcements! Watch this space for the address of the list.

5. Evaluation. Everyone who comes to class is expected to do the readings and participate in discussion. Registered students will have two other responsibilities:
   • Once during the semester, taking responsibility for reading one of the advanced papers ahead of time, leading the class discussion, and writing up a summary paper that discusses the paper and its relationship to the material in the course.
   • At the end of the semester, a project consisting of a paper-reviewing exercise: students will be on the "program committee" of a conference, reviewing one or more papers and recommending whether papers should be accepted, rejected, or accepted with revisions.

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   Course notes

   • A computational perspective
   • Language from a computational perspective
   • Automata and grammars
   • Parsing context-free grammars
   • Quantitative issues: probability and statistics
   • Basic elements of information theory
   • To be continued...