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  Music Processing

Prof. Dr. Meinard Müller

2 cred.h, benoteter certificate, credit: 2/2, ECTS studies, ECTS credits: 2,5, Sprache Englisch
Time and place: Mon 16:15 - 19:15, 3R4.04; comments on time and place: 8 sessions per term with each session covering 1,5 lectures = 90 + 45 minutes
starting 22.10.2012

Fields of study
WF WING-MA 1-4 (ECTS-Credits: 2,5)
WF CME-MA ab 2 (ECTS-Credits: 2,5)
WF SIM-DH 6-10 (ECTS-Credits: 2,5)
WF SIM-MA 1-4 (ECTS-Credits: 2,5)
WF WING-DH 6-10 (ECTS-Credits: 2,5)
WF EEI-MA 1-4 (ECTS-Credits: 2,5)
WF IuK-MA 1-4 (ECTS-Credits: 2,5)
WF IuK-MA-MMS-EEI 1-4 (ECTS-Credits: 2,5)

ECTS information:
Credits: 2,5

In this course, we discuss a number of current research problems in music processing or music information retrieval (MIR) covering aspects from information science and digital signal processing. We provide the necessary background information and give numerous motivating examples so that no specialized knowledge is required. However, the students should have a solid mathematical background and some background in digital signal processing. The lecture is accompanied by readings from textbooks or the research literature. Furthermore, the students are required to experiment with the presented algorithms using MATLAB.


  • Foundations in Mathematics

  • Digital Signal Processing

  • Interest in Music

Music signals possess specific acoustic and structural characteristics that are not shared by spoken language or audio signals from other domains. In fact, many music analysis tasks only become feasible by exploiting suitable music-specific assumptions. In this course, we study feature design principles that have been applied to music signals to account for the music-specific aspects. In particular, we discuss various musically expressive feature representations that refer to musical dimensions such as harmony, rhythm, timbre, or melody. Furthermore, we highlight the practical and musical relevance of these feature representations in the context of current music analysis and retrieval tasks. Here, our general goal is to show how the development of music-specific signal processing techniques is of fundamental importance for tackling otherwise infeasible music analysis problems.

The following video gives a brief impression about this course: http://www.youtube.com/watch?v=iY243jku0UA

Meinard Müller
Information Retrieval for Music and Motion

Additional information
Keywords: Audio, Music, Signal Processing, Fourier Transform, Feature Design, Fingerprinting, Beat Tracking, Music Information Retrieval
Expected participants: 15, Maximale Teilnehmerzahl: 30
www: http://www.youtube.com/watch?v=iY243jku0UA

Verwendung in folgenden UnivIS-Modulen
Startsemester WS 2012/2013:
Music Processing

Department: International Audio Laboratories Erlangen (AudioLabs)
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