Ling 354: Language and Computers (Fall 2009)
This course offers an introduction and overview of natural language processing and computational linguistics. Topics to be covered include speech recognition and generation, spelling and grammar checkers, information retrieval and search engines, conversational agents, and machine translation.
| Instructor | Rob Malouf |
|---|---|
| Time | MWF 13:00–13:50 |
| Location | EBA 412 |
Requirements
The final grade will be based on problem sets (10%), quizzes (30%), a midterm exam (30%), and a final exam (30%). The problem sets are a small part of the grade, but will be excellent practice for the quizzes and exams. Late homeworks will be accepted (with a grade penalty) for one week only after the deadline. Quizzes will be announced in advance, and I’ll drop the lowest quiz grade. If you can’t make it to a quiz or exam, let me know in advance! There will be no make-up exams without prior arrangements.Readings
The required textbook for this course is:Department of Linguistics. 2007. Language Files (10th Edtion). Ohio State University Press. http://linguistics.osu.edu/research/publications/languagefiles/It is for sale in the campus bookstore and at Amazon, etc. Updates and corrections can be downloaded from the authors’ website. Additional readings will be made available in class or via the “Resources” section of the course web page.
Proposed schedule:
- Week 1 Introduction
Background · What is computational linguistics? · What’s it good for? · Linguistics - Week 2–4 Processing words
Regular expressions · Finite state machines · Word structure · Computational morphology - Week 5–6 Processing sounds
Sound patterns · Phonological and orthographic rules · Speech synthesis - Week 7 Natural language processing
Tokenization · Corpora · Machine translation - Week 8 Midterm exam
- Week 9–10 Web searching
Document retrieval · Spiders · Web scraping · Google - Week 11–12 Information extraction
Parts of speech · Taggers · Grammars (Context free and beyond) - Week 13–14 Text mining
Document classification · Spam detection · Data mining · Question answering - Week 15 Review