Difference between revisions of "Music 254/CS 275b Spring 2022 Syllabus"
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Revision as of 19:06, 26 April 2022
Music 254/CS 275b "Computational Music Analysis "
Stanford University (Spring 2022).
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++), or Music21 (Python), or their preferred programming language/environment) students plan and design their own applications involving symbolic musical data.
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 firstname.lastname@example.org or email@example.com|
|Meeting times:||Tuesdays & Thursdays 1:30–3:00|
|Instructors:|| Eleanor Selfridge-Field (firstname.lastname@example.org)|
|Office Hours:||after class and by appointment on Zoom/Skype/Google Hangouts|
25% class participation, 75% project
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.|
See also Music 253/CS 275a Syllabus
|1||29 March, 31 March 2022||
Homework for new students
|2||5 Apr 2022||
Lectures: Approaches to melodic and other musical-similarity assessment
|2||7 Apr 2022|
|2||12 & 14 Apr 2022||
Cope, Emmy, Emily Howell Lectures (Style Synthesis)
|4||19 Apr 2022||
Lectures: Practical Realities of Research
|4||21 Apr 2022||
|5||26 April 2022||
Patterning and Coherence in Music
|5||28 April 2022||
|6||3 May 2022||
Rhythm and Meter
Programming for Humdrum files
|6||5 May 2022||
Sonority distributions by bass-line scale degrees
|7||10 May 2022||
Recent developments in MIR
|7||12 May 2022||
Recent Work in Harmonic Analysis
|8||17 May 2022||
Search Engines for Music
|8||19 May 2022||
|9a||24 & 26 May 2022||
|10||31 May 2022||
Project presentations in class.
|11||8 June 2022||
Project write-ups for students taking a degree in June 2022.
|12||9 June 2022||
Project write-ups for students continuing at Stanford.
- Data/Data entry in Humdrum (PDF slides)
- KernScores: digital library of scores in the **kern format
- : 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
- Humdrum to MIDI (PDF slides)
- Harmony II Key analysis
- keycor: harmonic structure plots.
- mkeyscape: harmonic structure plots.
- transpose: Transpose score to specific key or by interval.
Regular Expressions (Text-based searching)
Harmony-related Humdrum tools
- hint: Harmonic intervals.
- tntype: twelve-tone chord prototypes.
- key: Krumhansl-Schmuckler key-finding algorithm.
- keycor: generalization of key command.
- sonority: triadic chord descriptions of sonorities.
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
- Support tools:
- assemble: merge separate spines into single data stream.
- serialize: convert Humdrum data into single spine.
- humcat : concatenate multiple scores together (download data from web).
- ridx: remove various components of Humdrum file structure
- ditto: resolve meaning of null tokens.
- humsplit: split segmented Humdrum file streams into separate files.
- Unix tools:
- Support tools:
- Pitchmix and Markov analysis of composite sonorities
- Melody Tools available in Humdrum
- melody tools:
- support tools:
- graphics (unix):
General Policies and University Rules
General policies and university rules:
- Delivery times:
- Assignments: by the start of the class for which they are due.
- Project writeup: by 11 p.m. 7 or 11 June 2022 by 11p.
- Honor code: We will act and expect you to act according to the Stanford Honor Code.
- 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).
- Students in distress: Stanford offers an abundance of resources for students dealing with problems of a personal nature.
- Confidential support: (650) 736-6933
- Crisis hotline: (650) 725-9955
- Title IX questions: (650) 497-4955