LIN 105: Language Learning in Humans and Machines

Instructor Class Day/Time Location Email Office Hours Office
Masoud Jasbi Tue + Thu 1:10-2:30 Kerr 273 jasbi@ucdavis.edu Thu 4:30-5:30 Kerr 279

Schedule

Week Month Date Topic Content Resources Readings
1 Jan 6 Exploring Child Language Data
  1. talkbank.org and CHILDES
  2. CHILDES-db
  3. The BabyView Project
  4. Wordbank
  1. Clark (2016) Ch. 1 and 2
  2. Alishahi (2011). Ch. 1: Overview
  3. Frank (2023). Bridging the data gap between children and large language models
  4. Portelance, E. and Jasbi, M. (2024), The Roles of Neural Networks in Language Acquisition. Lang Linguist Compass
  5. Bunce et al: Cross-cultural Examination of Children's Language Experience
8
2 13
15
3 20 Learning Morphology 1. What is a Neural Network?
2. Gradient Descent, how neural networks learn
3. What is backpropagation really doing?
4. Backpropagation Calculus
  1. Alishahi (2011). Ch. 2: Morphological Acquisition
  2. Pinker and Ullman + McClelland and Patterson (2002): The past and future of past tense
  3. Rumelhart and McClelland (1986). On Learning the Past Tenses of English Verbs. PDF Research Group.
  4. Kirov and Cotterell. 2018. Recurrent Neural Networks in Linguistic Theory: Revisiting Pinker and Prince (1988) and the Past Tense Debate. TACL
  5. Weissweiler et al. (2023). Counting the Bugs in ChatGPT’s Wugs: A Multilingual Investigation into the Morphological Capabilities of a Large Language Model. EMNLP
22
4 27
29
5 Feb 3 Word Learning
  1. Alishahi (2011). Ch. 3: Word Learning
  2. Siskind (1996): A computational study of word-to-meaning mappings
  3. Frank, Goodman, Tenenbaum (2009): Using Speakers' Referential Intentions to Model Early Cross-Situational Word Learning
  4. Vong et al (2024): Grounded language acquisition through the eyes and ears of a single child
  5. Chang and Bergen (2022): Word Acquisition in Neural Language Models
5
6 10
12
7 17 Learning Syntax
  1. Alishahi (2011). Ch. 4
  2. Elman (1990): Finding Structure in Time
  3. Perfors, et al (2011): The Learnability of Abstract Syntactic Principles
  4. Huebner et al (2021): BabyBERTa
  5. Yedetore et al., (2023). How poor is the stimulus? Evaluating hierarchical generalization in neural networks trained on child-directed speech. ACL
19
8 24
26
9 Mar 3 Learning Phonology
5
10 9
11

Course Objectives

Objective Course Component
1 Introduce the foundations of computational learning models Readings, Lectures
2 Introduce the basic findings in children's language development Readings, Lectures
3 Practice critical and scientific thinking and research Assessment

Syllabus

Assessment
Research Skills 100 Points
Reserach Question and Bibliography 10 Points A one page bullet point presentation of the research question for your project and the papers you plan to read on it.
Introduction of the Research Question and Literature Review 20 Points A two page document presenting the research question and summarizing prior literature on it.
Research Proposal 30 Points A two page document presenting the research question, summarizing prior literautre, and proposing methods for your study and the results you expect.
Final Presentation 40 Points A 7 minute flash-talk presentation of your resarch question, prior literature, proposed methods for your study and results you expect followed with a 7 minute Q and A.
Policies
Groups You can do your research assignment individually or form groups with other students. Group submissions must also submit a separate page explaining author contributions. You can see an example of author contribution in scientific journal by clicking on this link. You should also mention whether authors have had roughly equal contribution in your judgment and the grade should be distributed equally or not. Common examples of unequal contribution are members missing meetings and work sessions of the group frequently or being completely absent and unresponsive until deadlines or even after. Disputes will be resolved on a case by case basis.
Late Submission Late assignments will be graded as though they were not late, but then 5% of the grade earned will be deducted for each day the assignment is late, with a maximum penalty of 50%. All late work must be turned in by the Friday before your final exam. This policy can be waived if lateness is due to medical reasons or other special circumstances.
Submission Format Submit your assignments using Canvas. Files should be in PDF. Typed assignments should use Times New Roman (12pt), 1 inch margins, 1.5 line spacing. Do not include your name or any identifying information in the assignment. In order to avoid grading biases, assignments are graded anonymously.
Grading We use the following grading scale:
A+ = 100-97 A = 97-93, A- = 93-90, B+ = 90-87, B = 87-83, B- = 83-80, C+ = 80-77, C = 77-73, C- = 73-70, D+ = 70-67, D = 67-63, D- = 63-60, F = 60-0.
For any submission, if you believe there have been grading mistakes, you can ask for re-grading. The assignment will be graded by a new grader and the second grade will be recorded.
Integrity We follow the UC Davis code of academic conduct. You are permitted to work together on the assignments. However, you must write up and submit your own unique assignments.
Accessibility Students who may need an academic accommodation based on the impact of a disability must initiate the request with the UC Davis Student Disability Center. Professional staff will evaluate the request, recommend reasonable accommodations, and prepare a letter of accommodation for the faculty. Students should contact the SDC as soon as possible since timely notice is needed to coordinate accommodations.
Addressing the Instructor I prefer Masoud and he/his/him for pronouns. No titles or last name needed.