Linguistics 5702: Cognitive Models of Language

This course covers formal mathematical cognitive models of how language comprehension, production and acquisition work in the brain, and behavioral and neuroimaging experimental evidence about these models.

Prerequisites: LING2000 or LING2000H or LING3701 or LING3701H or any linguistics course 4000 or above, or graduate standing.

Instructor: William Schuler

Meeting time: Wednesday and Friday 11:10am-12:40pm in Baker Systems 130

Web site: The updated syllabus, assignments, slides, etc. will be posted here, so check it regularly.

Textbook (optional): "Language in Mind: An introduction to Psycholinguistics," Julie Sedivy. Sinauer Associates, 2014. ISBN 978-0-87-893598-7.

Course Content:

Wk Assignments/readings for Tuesday Lecture: Wednesday Assignments/readings for Thursday Lecture: Friday
1 1/11 videos: probability, conditional probability 1/12 PS1 handout
overview, background, probability
1/13 videos: decision theory, predicates, quantifiers, lambda calculus 1/14
language and thought
2 1/18 1/19
1/20 video: Tom Mitchell on distributed representations 1/21
background: neural activation
3 1/25 PS1 due
tutorial: matrix multiplication
1/26 PS2 handout
background: associative memory
1/27 1/28
4 2/1 2/2
background: complex ideas
2/3 videos: sine wave speech (original), McGurk effect 2/4
speech, phonemes, hearing
5 2/8 PS2 due 2/9 PS3 handout
phone recognition
2/10 2/11
ambiguity and resolution
6 2/15 2/16
2/17 2/18
7 2/22 PS3 due 2/23 PS4 handout
background: hierarchic sequential prediction
2/24 step-though: sentence processing 2/25
sentence processing and left-corner parsing
8 3/1 3/2
memory bounds
3/3 papers: surprisal and memory 3/4
9 3/8 PS4 due 3/9 PS5 handout
3/10 3/11
unified surprisal and memory effects
10 (spring break) (spring break) (spring break) (spring break)
11 3/22
papers:left-corner surprisal
structural vs. deep neural surprisal
3/24 papers: left-corner surprisal in fMRI 3/25
fMRI surprisal and memory effects
12 3/29 3/30
quantifier scope
3/31 papers: speech segmentation 4/1
evidence for statistical learning, learning hierarchic rules
13 4/5 PS5 due
step-through: grammar induction
4/6 PS6 handout
Bayesian induction experiments
4/7 4/8
background: generalization (learning)
14 4/12 paper: statistical grammar induction 4/13
neural induction experiments
4/14 (no class)
15 4/19
learning meaning
4/21 PS6 due, video: alex the parrot, papers: Tomasello 4/22
models of grounding instinct in learning

Credit hours and work expectations: This is a 3-credit-hour course. According to Ohio State policy, students should expect around 3 hours per week of time spent on direct instruction (instructor content and Carmen activities, for example) in addition to 6 hours of homework (reading and assignment preparation, for example) to receive a grade of (C) average.

Course requirements:

Student participation requirements: Consistent engagement is expected. If any problems arise relative to attendance, please contact the instructor as soon as possible. Communication is important. You are encouraged to participate during class, ask questions, work on in-class problems in small groups, and share your experiences relative to the subjects and discussion that day.

Faculty feedback and response time:

Grading scale: OSU standard scheme
A A- B+ B B- C+ C C- D+ D
93% 90% 87% 83% 80% 77% 73% 70% 67% 60%

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