Syllabus for Ling 645/CMSC 723, Fall 1997
Introduction to Computational Linguistics

Course goals

• Survey. Familiarity with the major areas and problems in computational linguistics.
• Tools. Understanding of and experience with core techniques in natural language processing.
• Programming. Experience with writing programs to solve problems and explore empirical questions.

Course requirements

• Getting a Unix account and paying attention to course announcements via e-mail
• Weekly or near-weekly homework assignments, some including programming in Common LISP (40%)
• Two "hourly" exams (as opposed to a single midterm) (40%)
• Final exam (20%)

Outline of topics

• Overview of computational linguistics. Levels of natural language analysis. Elements of natural language processing systems.
• Automata and grammars. Finite-state formalisms, FST-based morphology, context-free grammars and variants.
• Parsing. Top-down and bottom-up methods. Dynamic programming and chart parsers. Time complexity.
• Features and augmented grammars. Features in syntactic formalisms. Unification.
• Natural language semantics. First-order predicate calculus. Lambda-reduction. Quantification. Entailment. Interpretation as abduction.
• Knowledge representation. Taxonomies and inheritance. KL-ONE variants and subsumption. Preference semantics.
• Corpus-based methods. Frequency, probability, and estimation. Types of corpus annotation. Classification paradigm and supervised learning.
• Application areas. Speech recognition. Message understanding. Machine translation.

  Philip Resnik                        Phone:   (301) 405-6760
  Department of Linguistics            Fax:     (301) 405-7104
  1401 Marie Mount Hall
  University of Maryland 
  College Park, MD 20742 USA

  By far the best way to reach me is by e-mail to resnik@umiacs.umd.edu.