Psycholinguistics I/II - 2020-2021

LING 640/641

Overview

This course is a year-long foundation course sequence in psycholinguistics, aimed at graduate students from any language science field. The course assumes no specific background in psycholinguistics, including experimentation or statistics. The first semester course also requires only limited background in formal linguistics. But all students should have a serious commitment to some area of language science, and relevant expertise that they can contribute to the class group. Psycholinguistics is a broad field. In principle, it includes all areas of the mentalistic study of language, including the various fields of so-called formal/theoretical linguistics, plus language acquisition and the neuroscience of language. And while we’re at it, why not throw in language disorders and second language acquisition for good measure! Due to this breadth, psycholinguistics can sometimes appear like a scientific archipelago – many interesting but disconnected islands. We will make no attempt to tour all of these islands in this course. Instead, we will focus on trying to understand the overall space, how the pieces fit together, and recurring themes and problems. The course will focus on:U

  • Understanding the landscape of psycholinguistics
  • Psycholinguistic thinking: finding good questions, evaluating evidence, resolving conflicts
  • Doing psycholinguistics: tools needed to carry out psycholinguistic research

In the Fall semester (LING 640) we will devote a lot of time to ‘model’ problems, such as speech categorization and word recognition, because these relatively simple cases allow us to probe deeply into psycholinguistic issues with limited linguistic overhead. 

In the Spring semester (LING 641) we will devote more attention to the relation between the syntax and semantics of sentences and language learning and language processing. 

Unprecedented

This is going to be an academic year like no other that we have known. The world is facing a global pandemic. There is an international economic crisis, with effects that reach most parts of society, including colleges and college towns. The US is facing extreme societal unrest. Many students are unable to come to campus. Many are unable to even enter the United States.

We have to adapt and be flexible in times like these.

We need to also keep an eye on sustainability. Whatever ‘normal’ will be in the future, we won’t be there for a while.

Geography

In other times we would be sitting around a big table and discussing. After class, we might continue discussing over lunch. This year we are separated by 12 time zones. We are evenly split among the College Park area, Europe, and China.  

Being so far apart will surely create challenges. Don’t be shy about mentioning them.

Health

The COVID-19 pandemic will likely be around us for a long while yet. Clearly, the health of yourself and those around you is of paramount importance.

Remember that mental health is an important element of good health, especially for graduate students. Be aware, and seek help if needed.

Connectivity

A research university thrives on connectivity. We have less of that now.

We see fewer people. We will have fewer spontaneous encounters. We will have fewer shared experiences. So we need to take extra steps to be connected.

Electronic connectivity could present additional challenges. Some may encounter difficulties accessing electronic resources. 

Individual and in person meetings

Individual and small group conversations are especially valuable right now. Seek them out!

I am very happy to have individual discussions. Just drop me a line. I can often adjust to your time zone constraints.

I welcome opportunities for in person meetings, for those who are local. I hope to have many outdoor meetings on campus this semester. The UMD campus is beautiful in the fall, and it is good for graduate students and faculty to be visibly active on campus.

 

 

 

 

 

 

Schedule – Fall

Mondays & Wednesdays, 12:00 – 1:30. Mostly online, URL shared with students.

August 31: Introduction. The psycholinguistic landscape

September 2: Some core concepts

September 7: NO CLASS – Labor Day Holiday

September 9: Development of Speech Perception

September 14:  Becoming a native listener

September 16: Distributional learning

September 21: Learning contrasts

September 23:

September 28: 

September 30: Neuroscience of speech perception and production

October 5: Word recognition

October 7: Active processing

October 12: Recognizing words in context

October 14:

October 19: Neuroscience of word recognition

October 21:

October 26: Word production

October 28:

NOVEMBER 1 – Daylight Savings Time ends

November 2:

November 4:

November 9:

November 11:

November 16:

November 18:

November 23:

November 25: NO CLASS – THANKSGIVING BREAK

November 30:

December 2:

December 7:

December 9:

December 14: FINAL CLASS OF SEMESTER

 

Requirements

This is graduate school. Your grade should not be your top concern here. You should be aiming to get a top grade, but your focus should be on using the course to develop the skills that will serve you well in your research. There will be no exams for this course. The focus of the course is on reading, discussing, writing and doing throughout the semester, and hence your entire grade will be based upon this. If you want to get the maximum benefit from this class (i.e. learn lots and have a grade to show for it at the end), you will do the following …

1. Come to class prepared, and participate (40% of grade).

Being prepared means having done some reading and thinking before coming to class. Writing down your initial thoughts or questions about the article(s) is likely to help. Although many readings are listed for this course, you are not expected to read them all from beginning to end. An important skill to develop is the ability to efficiently extract ideas and information from writing. Particpating in class discussions is valuable because it makes you an active learner and greatly increases the likelihood that you will understand and retain the material. You should also feel free to contact me outside of class with questions that you have about the material.

2. Think carefully and write clearly in assignments (60% of grade).

The assignments will come in a variety of formats. In lab assignments you will get hands-on experience with various research techniques in psycholinguistics, plus experience in reporting the results of those experiments. In writing assignments you will think and write about issues raised in class and in the assigned readings. The writing assignment may sometimes be due before the material is discussed in class: this will help you to be better prepared for class and to form your own opinions in advance of class discussion. In your writing it is important to write clearly and provide support for claims that you make.

f you are worried about how you are doing in the course, do not hesitate to contact me. Email is generally the most reliable way of reaching me.

Grade scale

 A 80-100%  B- 60-65%
 A- 75-80%  C+ 55-60%
 B+ 70-75%  C 50-55%
 B 65-70%  C- 45-50%

Note that even in the A range there is plenty of room for you to show extra initiative and insight. The threshold for A is deliberately set low, so that you have an opportunity to get additional credit for more creative work.

Teamwork

Written work should be submitted individually, unless the assignment guidelines state otherwise or you have made prior arrangements with the instructor, but you are strongly encouraged to work together on labs and homeworks in addition to group projects. Academic honesty includes giving appropriate credit to collaborators.  Although collaboration is encouraged, collaboration should not be confused with writing up the results of a classmate’s work – this is unacceptable. If you work as a part of a group, you should indicate this at the top of your assignment when you submit it.  

Assignments

The assignments for the course consist of a mix of shorter and longer written assignments, together with practical lab assignments.

The lab assignments are an important component of the course, and they are designed to give you first-hand experience with experimental and computational techniques used in psycholinguistic research. Typically you will have around 2 weeks for each lab assignment.

Discussion note #1: Marr’s (1982) discussion of visual perception highlights the “goal” of the computation. Does linguistic computation have a “goal”? Does Marr’s view on levels of analysis align with Chomsky’s contrasting of competence and performance? [See especially Marr, pp. 20-28, Chomsky pp. 3-15.]

Note that these classic distinctions from Chomsky and Marr are by no means the last word on these issues. Some argue that the distinctions are unnecessary, others argue for additional distinctions. In thinking about these issues, you may find it useful to apply the contrasts highlighted in class: (i) levels of analysis, (ii) tasks, (iii) mechanisms.

[Ignore this for now.] How does the debate about Bayesian models (Bowers & Davis 2012; Griffiths et al. 2012) align with Marr’s framework? Email colin@umd.edu before class on 9/2/20. Answer can be just a couple of paragraphs.

Lab #1A: Classic speech perception paradigms (due September 16th)

Lab #1B: Probing higher level encoding of speech (due September 28th)

Lab 2 – Lexical Decision

 


 

 

 

 

Notes

These are links to the slides used in the course. But note that they include some things that were not discussed in class, and in many cases the slides do not do justice to our extensive discussions in class.

 

 

Readings

This list will be updated over the course of the year.

Introduction (Fall)

Chomsky, N. (1965). Aspects of the theory of syntax. Cambridge, MA: MIT Press. [chapter 1]

Marr, D. (1982). Vision. Cambridge, MA: MIT Press. [excerpt]

Bowers, J. & Davis, C. (2012). Bayesian just-so stories in psychology and neurosciencePsychological Bulletin, 138, 389-414.

Griffiths, T., Chater, N., Norris, D., & Pouget, A. (2012). How the Bayesians got their beliefs (and what those beliefs actually are): Comment on Bowers and Davis (2012)Psychological Bulletin, 138, 415-422.

Bowers, J. & Davis, C. (2012). Is that what Bayesians believe? Reply to Griffiths et al. (2012)Psychological Bulletin, 138, 423-426.

Jackendoff, R. (2002). Foundations of language. Oxford University Press. [chapter 1, chapter 2, chapter 3, chapter 4]

Lewis, S. & Phillips, C. (2015). Aligning grammatical theories and language processing modelsJournal of Psycholinguistic Research, 44, 27-46.

Momma, S. & Phillips, C. (2018). The relationship between parsing and generation. Annual Review of Linguistics, 4, 233-254.

Speech Perception, Learning Sound Categories

Stager, C. & Werker, J. (1997). Infants listen for more phonetic detail in speech perception than word learning tasksNature, 388, 381-382. [This is one of the primary readings for the section of the course on phonetic/phonological representations. A very short, but very important study. Why are younger infants better than older infants, even on native-language contrasts?]

Vallabha, G. K., McClelland, J. L., Pons, F., Werker, J. F., & Amano, S. (2007). Unsupervised learning of vowel categories from infant-directed speechProceedings of the National Academy of Sciences, 104, 13273-13278. [This is an explicit implementation of the idea that is implicit in the papers by Maye et al. 2002 and Werker et al. 2007.]

Werker, J. (1994). Cross-language speech perception: Developmental change does not involve loss. In: Goodman & Nusbaum (eds.), The Development of Speech Perception. Cambridge, MA: MIT Press, pp:93-120. [Useful for Lab 1. This paper reviews in more details the reasons why Werker adopts a structure-adding view of phonetic development.]

Werker, J. (1995). Exploring developmental changes in cross-language speech perception. In L. Gleitman & M. Liberman (eds) Language: An Invitation to Cognitive Science, Vol 1 (2nd edn.), 87-106. [This paper is the best starting point for this section of the course. It presents an overview of Werker’s views on phonetic development up to 1995, including a straightforward study of her important cross-language experiments from the early 1980s.]

Werker, J. F., Pons, F., Dietrich, C., Kajikawa, S., Fais, L., & Amano, S. (2007). Infant-directed speech supports phonetic category learning in English and JapaneseCognition, 103, 147-162. [Analysis of what infants actually hear. It is presented as an argument for unsupervised distributional learning, but I suspect that it shows the opposite.]

 

Cognitive Neuroscience of Speech Perception

Näätänen et al. 1997. Language-specific phoneme representations revealed by electric and magnetic brain responsesNature, 385, 432-434.

Kazanina, N., Phillips, C., & Idsardi, W. 2006. The influence of meaning on the perception of speech soundsProceedings of the National Academy of Sciences, 103, 11381-11386.

van Turennout, M., Hagoort, P., & Brown, C. 1998. Brain activity during speaking: from syntax to phonology in 40 millisecondsScience, 280, 572-574.

 

Word Recognition

Altmann, G. 1997. Words and how we (eventually) find them. Chapter 6 of The Ascent of Babel. Oxford University Press. [A good introductory chapter.]

Marslen-Wilson, W. 1975. Sentence perception as an interactive parallel processScience, 189, 226-228.

Marslen-Wilson, W. 1987. Functional parallelism in spoken word recognitionCognition, 25, 71-102.

Boland, J. and Cutler, A. 1996. Interaction with autonomy: Multiple output models and the inadequacy of the Great DivideCognition, 58-309-320.

Dahan, D., Magnuson, J., & Tanenhaus, M. 2001. Time course of frequency effects in spoken word recognition: Evidence from eye-movementsCognitive Psychology, 42, 317-367.

Chen, L. & Boland, J. 2008. Dominance and context effects on activation of alternative homophone meaningsMemory and Cognition, 36, 1306-1323.

Kutas, M. & Federmeier, K. 2000. Electrophysiology reveals semantic memory use in language comprehension. Trends in Cognitive Sciences, 4, 463-470.

Lau, E., Phillips, C., & Poeppel, D. 2008. A cortical network for semantics: (de)constructing the N400. Nature Reviews Neuroscience, 9, 920-933.