LINGUIST 180
Introduction to Computational Linguistics
Autumn 2007

COURSE INFORMATION
Instructor
Dan Jurafsky, jurafsky@stanford.edu
Office: Margaret Jacks Hall (bld 460) 117
Office Hours: Tuesdays 11-12 and by appointment.
TA
Marie-Catherine de Marneffe, (mcdm@stanford.edu)
Office: Margaret Jacks Hall (bld 460) 113
Office hours: Wednesdays 2-3:30 and by appointment.
Time
Tuesdays and Thursdays, 9:30-10:45
Location
ART-4
Textbook

Selected online PDFs of chapters from the new edition of Jurafsky and Martin. 2007. Speech and Language Processing.
Description
This course is an introductory overview to the field of computer speech and language processing and computational linguistics. We will cover spoken language dialog systems, speech recognition and synthesis, web-based question answering, web search, finite-state methods, parsing and grammars, computational semantics, and discourse processing. The focus of this class is on writing scripts to use available online implementations of these applications, rather than on implementing complete applications themselves, although we will do some implementing of components. This class thus acts as a natural introduction to Stanford's rich offerings in computer language processing. Students are encouraged to continue with the classes listed in the the NLP, Speech and Dialog Processing, and Computational Linguistics Course List. Prerequisite: CS 106B/X
Required Work
  • Homeworks: 7 homeworks (Homework Collaboration Policy). Homework is due at 9:29am on the day it is due (i.e. before class starts).
    • LATE HOMEWORK WILL NOT BE ACCEPTED. But I will drop your lowest homework grade.
    • Homework Collaboration Policy: You may talk to anybody you want about the assignments and bounce ideas off each other. But you must write the actual homeworks and programs yourself.

  • Extra Credit. You can get extra credit by either doing all 7 homeworks (in which case your lowest homework counts as the extra credit one) or by participating in 2 hours of linguistic experiments. See details on how to get extra credit.

  • Readings: To be read before the class period in which they will be discussed. I will expect you to do a significant amount of textbook reading in this course.

  • Determination of final grade:
    • 84% best 6 homeworks out of 7
    • 16% class participation





SCHEDULE
Wk
Date
HW
Lec

Topic and Readings
1
 Sep 25
 Lec 1 (ppt)
Lec 1 (6up pdf)

Overview of Computational Linguistics, Regular Expressions

1
 Sep 27
Lec 2 (ppt)
Lec 2 (6up pdf)

Finite Automata
2
 Oct 2
 Lec 3 (ppt)
Lec 3 (6up pdf)

Spoken Dialogue Systems
2
 Oct 4
HW 1
(ELIZA) 		Lec 4 (ppt)
Lec 4 (6up pdf)

Spoken Dialogue Systems (II)

3
 Oct 9
Lec 5 (ppt)
Lec 5 (6up pdf)

N-grams
3
 Oct 11
HW 2
(DIAL) 		Lec 6 (ppt)
Lec 6 (6up pdf)

Part of Speech Tagging and Intro to Probabilistic Modeling

4
 Oct 16
Lec 7 (ppt)
Lec 7 (6up pdf)

Part of Speech Tagging (II)

4
 Oct 18
 HW 3
(LM) 		Lec 8 (ppt)
Lec 8 (6up pdf)

Hidden Markov Models
5
 Oct 23

Lec 9 (ppt)

Grammars and Parsing

5
 Oct 25
HW 4
(POS) 		Lec 10 (ppt)
Lec 10 (6up pdf) 		Grammars and Parsing (II)
6
 Oct 30
Lec 11 (ppt)
Lec 11 (6up pdf)

Machine Translation 1: Classical MT, Typology, and Start of Stat MT
6
 Nov 1
Lec 12 (ppt)
Lec 12 (6up pdf) 		Machine Translation 2: Statistical MT
7
 Nov 6

HW 5
(MT) 		Lec 13 (ppt)
Lec 13 (6up pdf)

Computational Lexical Semantics 1
7
 Nov 8
Lec 14 (ppt)
Lec 14 (6up pdf)

Computational Lexical Semantics 2
8
 Nov 13
HW 6
(SEM)

Dan sick today class cancelled
8
 Nov 15
 Lec 15 (ppt)

Discourse (Marie guest lecture)

Nov 20

Thanksgiving Break

Nov 22

Thanksgiving Break
9
 Nov 27
 Lec 16 (ppt)
Lec 16 (6up pdf)

Web-Based Question Answering
9
 Nov 29
HW 7
(DISC) 		Lec 17 (ppt)
Lec 17 (6up pdf)

Text-to-Speech Synthesis
10
 Dec 4
Lec 18 (ppt)
Lec 18 (6up pdf)

ASR 1
10
 Dec 6
Lec 19 (ppt)
Lec 19 (6up pdf)

ASR 2