Difference between revisions of "Music 254/CS 275b Spring 2023 Syllabus"

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<font size=+1><b>Music 254/CS 275b "Computational Music Analysis "  <br> Stanford University (Spring 2023).</b></font>
 
<font size=+1><b>Music 254/CS 275b "Computational Music Analysis "  <br> Stanford University (Spring 2023).</b></font>
  
This music information retrieval course (previously listed as "Music Query, Analysis, and Style Simulation") builds on the foundation of [[Music 253|Music 253/CS 275A]] (Symbolic Musical Information). Using an open-source analysis platform (such as the [https://github.com/humdrum-tools/humdrum-tools Humdrum Toolkit] (unix/bash shell), [[Humdrum Extras]] (C++), [[HumdrumR]], or [[Music21]] (Python), or their preferred programming language/environment) students plan and design their own applications involving symbolic musical data.  See Online Resources after syllabus.
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This music information retrieval course (previously listed as "Music Query, Analysis, and Style Simulation") builds on the foundation of [[Music 253|Music 253/CS 275A]] (Symbolic Musical Information). Using an open-source analysis platform (such as the [https://github.com/humdrum-tools/humdrum-tools Humdrum Toolkit] (unix/bash shell), [[Humdrum Extras]] (C++), [https://humlib.humdrum.org humlib], [https://verovio.humdrum.org VHV]. [[HumdrumR]], or [[Music21]] (Python), or their preferred programming language/environment) students plan and design their own applications involving symbolic musical data.  See Online Resources after syllabus.
  
 
The first four weeks cover basic areas of music analysis and retrieval and
 
The first four weeks cover basic areas of music analysis and retrieval and

Revision as of 14:01, 18 May 2023


Music 254/CS 275b "Computational Music Analysis "
Stanford University (Spring 2023).

This music information retrieval course (previously listed as "Music Query, Analysis, and Style Simulation") builds on the foundation of Music 253/CS 275A (Symbolic Musical Information). Using an open-source analysis platform (such as the Humdrum Toolkit (unix/bash shell), Humdrum Extras (C++), humlib, VHV. HumdrumR, or Music21 (Python), or their preferred programming language/environment) students plan and design their own applications involving symbolic musical data. See Online Resources after syllabus.

The first four weeks cover basic areas of music analysis and retrieval and introduce basic principles of using the Humdrum Toolkit. Students may be assigned individual reading assignments pertinent to their research topic areas. The remaining six weeks are spent on individual project development, with weekly reports and discussions. Extensive help is available in the lab during hours allotted to class time. Students give verbal and written reports on their research at the end of the quarter. Some projects may be appropriate for continuation in independent-study modules.

For class Zoom link
Please contact esfield@stanford.edu or craig@ccrma.stanford.edu
Meeting times: Tuesdays & Thursdays 1:30–3:00
Location: Online
Instructors: Eleanor Selfridge-Field (esfield@stanford.edu)
Craig Sapp(craig@ccrma.stanford.edu)
Office Hours: after class and by appointment on Zoom/Skype/Google Hangouts
Credits: 2–4
Grading:

25% class participation, 75% project

  • Project proposal: 2+ pages, due Thursday. 20 April 2023
  • Project progress report: 2+ pages, Thurs. 11 May 20223
  • Project presentation in class: Tues. 6 June 2023
  • Project writeup: 10–20 pages
    • Graduating in June 2023: Due on 9 June 2023 11:59pm.
    • Not graduating: Due on 13 June 2023 11:59pm.
Website: music254.stanford.edu
wiki.ccarh.org/wiki/Music 254 Overview of topics presented in Music 254.
Prerequisites: Completion of Music 253/CS 275b, or demonstrated ability to use notation and sound software and associated requirements.
Textbook: E. Selfridge-Field, ed., Beyond MIDI: The Handbook of Musical Codes (MIT Press, 1997). Available online by permission of the publisher.



Syllabus

Go to week: Harmony 1 | Melody 2 | Rhythm 3 | Harmony 4 | RegEx 5 | Programming 6 | 7 | 8

See also Music 253/CS 275a Syllabus

Week 1

Week Dates Topics
1
4 April, 6 April 2023

Lectures


Homework for new students

Week 2

Week Dates Topics
2
11 Apr 2023

Lectures: Approaches to melodic and other musical-similarity assessment

2 13 Apr 2023

Week 3

Week Dates Topics
2
18 & 20 Apr 2023

AI Audio Compositions, Emily Howell Lectures (Style Synthesis)

Week 4

Week Dates Topics
4
25 Apr 2023

Lectures: Practical Realities of Research

4 27 Apr 2023

Audio Similarity

Week 5

Week Dates Topics
5
2 May 2023

Audio similarity


5 4 May 2023


Regular Expressions


Week 6

Week Dates Topics
6
9 May 2023

Compositional schemata

  • Quality Control in Research: Heinz Roggenkemper (guest lecture)
  • Project report: Adaptive tuning (Shray Alag)

Counterpoint II

Rhythm and Meter

Programming for Humdrum files

6 11 May 2023
  • Project reports: Leon Bi and Charles Tsai (DJ transitions); Sammy Park (Guqin Digital Scores); Dominic DeMarco (Orchestral Pairings in Band Music)

Sonority distributions by bass-line scale degrees

Week 7

Week Dates Topics
7 16 May 2023
  • Wolfgang Drescher, guest lecture
  • Katherine Wong, guest presentation
7 18 May 2023

Recent developments in MIR

07A_RecentWork_SymbolicMIR_2021.ppt 07A. Recent Work in Symbolic MIR] Recent Work in Harmonic Analysis

Week 8

Week Dates Topics
8 23 May 2023

Recent Research (and Challenges) in MIR

Project development

8 25 May 2023
  • Music and AI: Julia Mills (guest lecture)

Project development

Week 9

Week Dates Topics
9a 30 May, 1 June 2023

Counterpoint

MEI

  • MEI (Music Encoding Initiative) Release 2.0

Week 10

Week Dates Topics
10 6 June 2023

Project presentations in class.

11 9 June 2023

Project write-ups for students taking a degree in June 2023.

12 13 June 2023

Project write-ups for students continuing at Stanford.

Online resources for this class

Data/Data entry

  • Data/Data entry in Humdrum (PDF slides)
    • KernScores: digital library of scores in the **kern format
      • [1] introduction to KernScores
      • [2] shortcuts to data in KernScores
      • [3] browse collections in KernScores
    • [4]: Josquin Research Project: digital library of early Renaissance polyphony
    • xml2hum: MusicXML to Humdrum converter
    • mid2hum: MIDI to Humdrum converter (works in many cases, but better to convert MIDI first to MusicXML then import).

Humdrum & MIDI


Harmony II


Regular Expressions (Text-based searching)

Harmony-related Humdrum tools

Rhythm and score manipulation tools

  • Rhythm Tools available in Humdrum
    • timebase: create uniform duration for each Humdrum file data line.
    • beat: label metric beats in Humdrum file.
    • gettime: calculate performance time in seconds (according to tempo markings).
    • thrux: expand repeats to performance sequence
    • minrhy: identify minimum integral rhythmic unit in score
    • assemble: merge parts into a single score
    • partjoin: automation script to merge parts into a single score (preserves grace notes, uses minrhy and timebase)
    • ditto/dittox: resolve null tokens
    • hgrep: search for patterns in Humdrum file data.

Performance analysis tool

Melody Lab

  • Melody Tools available in Humdrum
    • melody tools:
    • support tools:
      • kern: remove rhythms from note data.
      • myank Yank measures from a full score.
      • extract: extract spines from Humdrum file.
      • extractx: Humdrum Extras version of extract
      • hgrep: Humdrum-aware greep.
      • autostem: automatic stemming of notes.
    • unix:
      • head: show only starting lines of text.
      • grep: search text for generalized regular expressions.
      • egrep: enhanced grep (adds additional wildcards).
      • sed: Stream editor (search and replace).
    • graphics (unix):
      • pstopnm: a converter from PostScript to bitmaps.
      • convert: Imagemagick tool for manipulating images.
      • ps2pdf: convert PostScript into PDF files.

General Policies and University Rules

General policies and university rules:

  1. Delivery times:
    1. Assignments: by the start of the class for which they are due.
    2. Project writeup: by 11 p.m. 7 or 11 June 2022 by 11p.
  2. Honor code: We will act and expect you to act according to the Stanford Honor Code.
  3. Students with disabilities: Students who may need an academic accommodation based on the impact of a disability must initiate the request with the Student Disability Resource Center (SDRC) located within the Office of Accessible Education (OAE). SDRC staff will evaluate the request with required documentation, recommend reasonable accommodations, and prepare an Accommodation Letter for faculty dated in the current quarter in which the request is being made. Students should contact the SDRC as soon as possible since timely notice is needed to coordinate accommodations. The OAE is located at 563 Salvatierra Walk (phone 723-1066).
  4. Students in distress: Stanford offers an abundance of resources for students dealing with problems of a personal nature.
    1. Confidential support: (650) 736-6933
    2. Crisis hotline: (650) 725-9955
    3. Title IX questions: (650) 497-4955