Postgraduate Course: Music Informatics (INFR11079)
|School||School of Informatics
||College||College of Science and Engineering
||Availability||Available to all students
|Credit level (Normal year taken)||SCQF Level 11 (Postgraduate)
|Home subject area||Informatics
||Other subject area||None
||Taught in Gaelic?||No
|Course description||The course covers the principal theories, techniques and algorithms developed recently to give computational accounts of how musical phenomena can be analysed, generated and mediated with machine support or collaboration. The emphasis is on concepts, rather than tools, but the ideas have wide applicability. The state of the art is presented in selected areas.
Entry Requirements (not applicable to Visiting Students)
||Other requirements|| This course is open to all Informatics students including those on joint degrees. For external students where this course is not listed in your DPT, please seek special permission from the course organiser.
Students are normally expected to have some level of musical background, for example a school qualification such as Higher or A level music, or a background in musical performance.
|Additional Costs|| None
Information for Visiting Students
|Displayed in Visiting Students Prospectus?||Yes
Course Delivery Information
|Delivery period: 2013/14 Semester 2, Available to all students (SV1)
||Learn enabled: No
|Course Start Date
|Breakdown of Learning and Teaching activities (Further Info)
Lecture Hours 20,
Summative Assessment Hours 2,
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
|Breakdown of Assessment Methods (Further Info)
||Hours & Minutes
|Main Exam Diet S2 (April/May)||2:00|
Summary of Intended Learning Outcomes
|1 - Explain the relationship between various music representations
2 - Explain the use of musical grammars in characterising musical structures.
3 - Give algorithms for the determination of basic metrical and tonal aspects of traditional western music.
4 - Show how statistical information about music can be used to characterise particular styles.
5 - Contrast the different approaches to automated generation of music in specific styles.
6 - Provide a computational account of the exchange of musical and other information between musical agents.
|Written Examination 70|
Assessed Assignments 30
Oral Presentations 0
Assessment will by written exam (70%) and a written survey report analysing recent research on a topic agreed with the lecturer (30%).
If delivered in semester 1, this course will have an option for semester 1 only visiting undergraduate students, providing assessment prior to the end of the calendar year.
* Physics of music vs musical perception,
* Music Representation
Basic Local Analysis Algorithms
* Beat tracking; score following
* Tonal centre (Longuet-Higgins, Bolzano)
Information Theory, Statistical methods
* Characterising musical style
* Music generated by statistical constraints (Xenakis)
Machine Composition in a Given Style
Musical Agents and Interaction
Relevant QAA Computing Curriculum Sections: Not yet available
||Not yet available
Timetabled Laboratories 0
Non-timetabled assessed assignments 24
Private Study/Other 56
|Course organiser||Dr Iain Murray
Tel: (0131 6)51 9078
|Course secretary||Ms Katey Lee
Tel: (0131 6)50 2701
© Copyright 2013 The University of Edinburgh - 13 January 2014 4:28 am