/mcp

A repo to support PSYC/COGS 397 Music Computing and Psychology

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mcp

A repo to support PSYC/COGS 397 Music Computing and Psychology

Syllabus for Seminar in Music Computing and Psychology

Meeting time: Thursday 1:10-4:00 pm
Location: Maginnes Hall, room 103 for discussions; Digital Media Classroom for assignment work
Instructor: Dr. Tom Collins
Office: Chandler-Ullmann 223
Phone: 610-758-4209
Email: toc215@lehigh.edu
Office Hours: Friday 1:10-3:00 pm

Table of Contents

Course Overview
Learning Objectives
Methods of Assessment
Grading
Course Policies
Accommodations for Students with Disabilities
Required Reading
Tentative Schedule

Course Overview

This seminar examines key papers and concepts from the fields of music psychology and music computing. Development of music processing and programming skills is part of the course, enabling a fuller exploration of the intersection of the two fields. We will be addressing questions such as: Why is music cognition important to psychology as a whole? How might computing and psychology combine to widen participation in music, and to what end?

You will be able to personalize your learning by selecting music/topics to explore more fully in assignments.

Classes will start with a discussion of one or more chapters/papers (1-1.5 hrs), followed by an exploratory coding session and/or assignment work (1-1.5 hrs). Each topic will be introduced by a short, instructor-led discussion of a review chapter, before the discussion leader coordinates our discussion of 1-2 research articles. Additionally, each student will present their Web-based demo in the last-but-one class.

As a seminar course, the entire class is responsible for reading the assigned materials closely and thoughtfully before each meeting. Assessment of performance is designed to reward students who come to class prepared to ask questions, raise issues, and generally contribute to the discussion.

Learning Objectives

Upon successful completion of this course, students will be able to:

  • Discuss findings/achievements associated with the fields of music psychology and music computing, both broadly and in detail, and displaying knowledge of benefits and limitations of the techniques via which findings/achievements were realized.
  • Adapt existing code or write their own in order to process music representations and publish interactive Web pages.
  • Explain key areas of music cognition and how different experimental approaches have provided important insights.

Methods of Assessment

Participation in Class Discussion.........................26%
Leading Class Discussion..................................13%
Written Discussion Points.................................13%
Assignment 1 - Representations or Hive Chimes.............10%
Assignment 2 - Web-based Essay............................10%
Assignment 3 - Web-based Demo
 Time and Effort..........................................13%
 In-class Presentation.....................................5%
 Quality of Finished Demo.................................10%
  • Participation in Class Discussion: This is a discussion-based course. At each class, it is expected you will participate in the discussion (which requires regular attendance). Participation includes asking for clarification on any aspects of the readings you did not understand, as well as making more in-depth comments about the broader meaning of the work. For each paper, you should be prepared to answer the following questions (and should expect to be called on to do so!):
    • What was the goal of the paper? (research question or hypothesis)
    • How did they address the goal? (specific methods and statistical analyses)
    • What did they find? (results)
    • What did they conclude? (specific conclusions and broader implications)
  • Leading Class Discussion: For each class that you are assigned as discussion leader (see initials in Schedule below), it will be your responsibility to keep the conversation moving. You will get access to your peer's written discussion points shortly after they are due, and you can use these to engage your fellow students in exchanging ideas and views. You will receive your grade based on whether you keep the discussion moving, actively engage all members of the group, move through the main points of the paper (described in the above section), and guide deeper analysis of the work by incorporating other's discussion points as well as your own probing questions. You will receive feedback each time you lead discussion to help you improve.
  • Written Discussion Points: For each assigned reading you will post a discussion question or comment on the Course Site at least 24 hours in advance of the class. These posts will form the basis of our discussion. These posts should not involve clarification questions, but should focus on one of the following:
    • Critical Evaluation. Critiquing the arguments, methods, assumptions, or conclusions of the authors;
    • Implications. Relate the findings to the broader world, or generate a novel experimental prediction based on the findings;
    • Integration/Synthesis. Draw connections between the present reading and other ideas or readings, highlighting points of agreement or conflict.
  • Assignment 1 - You have a choice for this assignment:
    • Select a song/piece of music that you like, obtain audio and symbolic representations of it, annotate some repeated patterns, and visualize the whole thing in the PatternViewer application, or;
    • Hive Chimes. This is a sonification project, which basically means turning non-musical data into sounds for the sake of analysis and/or enjoyment. There is a folder in the repo (assignments/1/hive_chimes) where data about bees going in and out of a hive appear. Your task is to come up with a strategy for how to turn these events into Tone.js sounds, such that trends in the data can be heard. To start you off, assignments/1/hive_chimes/index.html shows one way to build an instrument with some wind chime samples (try opening it in Firefox).
  • Assignment 2 - Web-based Essay: Based on your developing Web programming skills and course reading/research to date (beginning of March), Assignment 2 provides the opportunity to write an essay (1,000 words maximum) on one of the following topics:
    • "Top 5" score-following apps, including links, descriptions, and justification of rank;
    • "Top 10" music databases, including links, descriptions, and justification of rank;
    • Exposition of 1 book, 1 patent, or 2 papers;
    • Original empirical research proposal;
    • Profile (Wikipedia-style) of 2 figures from music computing and psychology;
    • Glossary of terms from music computing and psychology;
    • Annotated bibliography;
    • Topic of your own devising, by arrangement.
  • Assignment 3 - Web-based Demo: Based on what you have learnt in the course to date (just after Spring Break), Assignment 3 provides the opportunity to develop a Web-based demo of a music-psychological phenomenon or an interface that does or encapsulates something related to one of the topics we have covered. You will be assessed on the time and effort that goes into making the demo, how well you present and explain it and its construction in the last-but-one class of semester, and my appraisal of the demo's overall quality. Assignments of sufficient quality may be published, with your permission and under your authorship, at http://tomcollinsresearch.net, in the spirit of https://musiclab.chromeexperiments.com/

Grading

Grades will be based on the following points system: x ≥ 93 -> A; 90 ≤ x < 93 -> A−; 87 ≤ x < 90 -> B+; 83 ≤ x < 87 -> B; 80 ≤ x < 83 -> B− 77 ≤ x < 80 -> C+; 73 ≤ x < 77% -> C; 70 ≤ x < 73 -> C−; 67 ≤ x < 70 -> D+; 63 ≤ x < 67 -> D; 60 ≤ x < 63 -> D−; x < 60% -> F.

Course Policies

Course Site and GitHub: This course will make use of both a Course Site (https://coursesite.lehigh.edu) and, to help teach the principles of version control, a GitHub repository (https://github.com/tomthecollins/mcp). Version control helps people to work on the same (coding) project simultaneously. The Principles of Our Equitable Community: Lehigh University endorses The Principles of Our Equitable Community (http://bit.ly/2bFMU5v). I expect each member of this class to acknowledge and practice these Principles. Respect for each other and for differing viewpoints is a vital component of the learning environment inside and outside the classroom. Lehigh University is committed to diversity, inclusion and engagement. Students are expected to join in class discourse with integrity of scholarship and to show respect for others.

Academic Integrity: It is your responsibility to make sure that your work meets the standard of academic honesty set forth in the Lehigh Code of Conduct (http://studentaffairs.lehigh.edu/content/code-conduct). Academic dishonesty on assignments will be treated as an extremely serious matter, and will be reported to The Office of Student Conduct & Community Expectations. Plagiarism occurs when material is taken from a source without proper citation. If you quote something directly (i.e., if you use another author's exact words), you must use quotation marks. If you borrow an idea and reword it, you must report your source and include it in your reference list. If you use somebody else's code, you must acknowledge this use where it occurs and in any readme file. It is never permissible to turn in work that has been copied from another student or copied from a source (including the Internet) without properly acknowledging that source. That said, in this course you are expected to develop your work in consultation with Dr. Collins and with one another, to make the most of differing backgrounds and areas of expertise that students and I bring to this interdisciplinary seminar. There is no such thing as a "stupid question" in this class.

General Considerations:

  1. Please arrive for class on time. It is disruptive to both me and your classmates if you are late.
  2. Please put away silenced cells phones and do not text or use social media in class.
  3. Put in the time to do well. Make sure that you allocate a sufficient amount of time to reading, writing, and coding.

Deadlines: No work will be accepted after the due date. If you have an emergency that means you will not be able to complete an assignment on time, you need to contact Dr. Collins before the due date to discuss the possibility of an extension. It is up to Dr. Collins' discretion to provide an extension, and there is no guarantee that one will be granted.

Accommodations for Students with Disabilities

If you have a disability for which you are or may be requesting accommodations, please contact both your instructor and the Office of Academic Support Services, University Center C212 (610-758-4152) as early as possible in the semester. You must have documentation from the Academic Support Services office before accommodations can be granted.

Required Reading

The following list is roughly in the order in which you should read the items. We will use two books, referred to on the Schedule overleaf as "Deutsch" and "Huron". The first, Deutsch (2013), is a general guide to music psychology, consisting of chapters contributed by different experts in the field, and so we will use this to help place specific research papers in their broader context. The second, Huron (2006), concerns the topic of musical expectancy, which we will discuss toward the end of semester, and so you may wish to begin reading it now in case you want to make use of it in Assignments 2 or 3. The first two books listed below are optional reading. They are very accessible, and so ideal if you are a novice in music psychology (read Levitin, 2007), music computing (read Loy, 2006), or both!

  • Levitin, D. J. (2007). This is your brain on music: The science of a human obsession. Plume/Penguin, New York, NY. (Available for cost of shipping on Amazon.)
  • Loy, G. (2006). Musimathics: The mathematical foundations of music. (2 Vols.). MIT Press, Cambridge, MA. (Available in the Library in hardcopy https://asa.lib.lehigh.edu/Record/957653 or as ebook https://asa.lib.lehigh.edu/Record/1486305 , https://asa.lib.lehigh.edu/Record/10615305 .)
  • Deutsch, D. (2013). The psychology of music, 3rd ed. Academic Press, San Diego, CA. (Available in the Library in hardcopy at present https://asa.lib.lehigh.edu/Record/10734338 or as ebook https://asa.lib.lehigh.edu/Record/10733074 .)
  • Huron, D. (2006). Sweet anticipation: Music and the psychology of expectation. MIT Press, Cambridge, MA. (Available in the Library as ebook https://asa.lib.lehigh.edu/Record/1486325 .)
  • Zuk, J., Benjamin, C., Kenyon, A., & Gaab, N. (2014). Behavioral and neural correlates of executive functioning in musicians and non-musicians. PloS one, 9(6), e99868.
  • Ferreri, L., Aucouturier, J. J., Muthalib, M., Bigand, E., & Bugaiska, A. (2013). Music improves verbal memory encoding while decreasing prefrontal cortex activity: an fNIRS study. Frontiers in human neuroscience, 7.
  • Collins, T. (2011). Improved methods for pattern discovery in music, with applications in automated stylistic composition (Doctoral dissertation). Retrieved from http://oro.open.ac.uk/30103/ (Only need to read Appendix B for this course. Appendix A provides helpful mathematical definitions.)
  • Shepard, R. N. (1964). Circularity in judgments of relative pitch. Journal of the Acoustical Society of America, 36, 2346-2353.
  • Grachten, M., & Widmer, G. (2012). Linear basis models for prediction and analysis of musical expression. Journal of New Music Research, 41(4), 311-322.
  • Collins, T., & Laney, R. (2017). Computer–generated stylistic compositions with long–term repetitive and phrasal structure. Journal of Creative Music Systems, 1(2).
  • Krebs, F. Böck, S, & Widmer, G. (2013). Rhythmic pattern modeling for beat and downbeat tracking in musical audio. Proceedings of the International Society for Music Information Retrieval Conference (pp. 227-232). Curitiba, Brazil.
  • Deutsch, D. (1980). The processing of structured and unstructured tonal sequences. Perception and Psychophysics, 28, 381-389.
  • Böck, S., & Schedl, M. (2012). Polyphonic piano note transcription with recurrent neural networks. Proceedings of the International Conference on Acoustics, Speech, and Signal Processing, (4 pages). Kyoto, Japan.
  • Krumhansl, C. L., & Kessler, E. J. (1982). Tracing the dynamic changes in perceived tonal organization in a spatial representation of musical keys. Psychological Review, 89, 334-368.
  • Sapp, C. S. (2005). Visual hierarchical key analysis. ACM Computers in Entertainment, 3(4), 1-19.
  • Wang, A. L.-C., & Smith III, J. O. (2006). US Patent No. 6,990,453. Washington, DC: U.S. Patent and Trademark Office. (Filed July 31, 2000.)
  • Meredith, D., Lemström, K., & Wiggins, G. A. (2002). Algorithms for discovering repeated patterns in multidimensional representations of polyphonic music. Journal of New Music Research, 31, 321-345.
  • Collins, T., Arzt, A., Frostel, H., & Widmer, G. (2016). Using geometric symbolic fingerprinting to discover distinctive patterns in polyphonic music corpora. In D. Meredith (Ed.), Computational Music Analysis (pp. 445-474). Berlin: Springer.
  • Deutsch, D., Henthorn, T., and Lapidis, R. (2011). Illusory transformation from speech to song. Journal of the Acoustical Society of America, 129, 2245-2252.
  • Barrett, F. S., & Janata, P. (2016). Neural responses to nostalgia-evoking music modeled by elements of dynamic musical structure and individual differences in affective traits. Neuropsychologia, 91, 234-246.

Tentative Schedule

Class. Date, Leader Topics Reading Requirements and Deadlines
1. 1/25/18, JD Does Music Make You Clever? Syllabus Overview and Web-based Music Demos (Tone.js, NexusUI, and VexFlow) Zuk et al. (2014), Ferreri et al. (2013)
Coding: HTML, JavaScript, and PHP
2. 1/31/18, MB Audio Representations of Music Ch. 1 of Deutsch, Collins (2011, pp. 327-340)
Coding: Signal processing in Matlab and Tone.js; Audacity and Sonic Visualiser
3. 2/8/18, TC Symbolic Representations of Music Ch. 6 of Deutsch, Collins (2011, pp. 341-366)
Coding: MuseScore, MCStylistic, and PattDisc
4. 2/15/18, AS Pitch Ch. 4 and 5 of Deutsch, Shepard (1964)
Coding: PatternViewer toward Assignment 1 and/or student-led
5. 2/22/18, PDM Automatic Generation of Music Ch. 8 of Deutsch, Grachten and Widmer (2012), Collins and Laney (2017)
Coding: PatternViewer toward Assignment 1 and/or student-led
2/26/18 at 12 noon Assignment 1 due
6. 3/1/18, AGR Rhythm, Beat-tracking, and Quantization Ch. 9 of Deutsch, Krebs, Böck, and Widmer (2013)
Coding: Toward Assignment 2 and/or student-led
7. 3/8/18, CD F0-estimation, Transcription, and Training Deutsch (1980), Böck & Schedl (2012)
Coding: Toward Assignment 2 and/or student-led
3/12/18 Spring Break
3/19/18 at 12 noon Assignment 2 due
8. 3/22/18, MG Tonality Ch. 7 of Deutsch, Krumhansl and Kessler (1982), Sapp (2005)
Coding: Coding hereafter is aimed toward Assignment 3 and/or student-led
9. 3/29/18, TV Fingerprinting (or "How Shazam Works") Wang and Smith III (2006/2000), Arzt, Böck, and Widmer (2012)
10. 4/5/18, MI Repetition, Repetition, Repetition Meredith, Lemström, and Wiggins (2002), Collins, Artz, Frostel, and Widmer (2016)
11. 4/12/18, PDM Musical Expectation I Ch. 1-6 of Huron
12. 4/19/18, AT Musical Expectation II Ch. 7-11 of Huron, Barrett and Janata (2016)
13. 4/26/18, TC Presentations
4/30/18 at 12 noon Assignment 3 due
14. 5/3/18, TC Musical Expectation III Ch. 12-17 of Huron

Acknowledgments

With thanks to Dr. Carlisle for help with course design.

Last modified: January 30, 2018