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DEGREE REGULATIONS & PROGRAMMES OF STUDY 2013/2014
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DRPS : Course Catalogue : School of Informatics : Informatics

Postgraduate Course: Music Informatics (INFR11079)

Course Outline
SchoolSchool of Informatics CollegeCollege of Science and Engineering
Course typeStandard AvailabilityAvailable to all students
Credit level (Normal year taken)SCQF Level 11 (Postgraduate) Credits10
Home subject areaInformatics Other subject areaNone
Course website http://course.inf.ed.ac.uk/mi Taught in Gaelic?No
Course descriptionThe 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)
Pre-requisites Co-requisites
Prohibited Combinations 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
Pre-requisitesNone
Displayed in Visiting Students Prospectus?Yes
Course Delivery Information
Delivery period: 2013/14 Semester 2, Available to all students (SV1) Learn enabled:  No Quota:  None
Web Timetable Web Timetable
Course Start Date 13/01/2014
Breakdown of Learning and Teaching activities (Further Info) Total Hours: 100 ( Lecture Hours 20, Summative Assessment Hours 2, Programme Level Learning and Teaching Hours 2, Directed Learning and Independent Learning Hours 76 )
Additional Notes
Breakdown of Assessment Methods (Further Info) Written Exam 70 %, Coursework 30 %, Practical Exam 0 %
Exam Information
Exam Diet Paper Name 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.
Assessment Information
Written Examination 70
Assessed Assignments 30
Oral Presentations 0

Assessment
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.
Special Arrangements
None
Additional Information
Academic description Not entered
Syllabus Background
* Physics of music vs musical perception,
* Music Representation

Basic parameters

Basic Local Analysis Algorithms
* Beat tracking; score following
* Tonal centre (Longuet-Higgins, Bolzano)

Musical Grammars

Musical Similarity

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
Transferable skills Not entered
Reading list Not yet available
Study Abroad Not entered
Study Pattern Lectures 20
Tutorials 0
Timetabled Laboratories 0
Non-timetabled assessed assignments 24
Private Study/Other 56
Total 100
KeywordsNot entered
Contacts
Course organiserDr Iain Murray
Tel: (0131 6)51 9078
Email: I.Murray@ed.ac.uk
Course secretaryMs Katey Lee
Tel: (0131 6)50 2701
Email: Katey.Lee@ed.ac.uk
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