The lecture has the following format:
For further information, please contact Prof. Dr. Meinard Müller.
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.
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. 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.
The general area of Music Processing covers a wide range of subfields and tasks such as music anaylsis, music synthesis, music information retrieval, computer music composition, performance analysis, or audio coding not to speak from close connections to other disciplines such as musicology or library sciences. In this course, we present a selection of topics with an emphasis on music analysis and retrieval.
The course "Music Processing - Analysis" is closely related to the course "Music Processing - Synthesis" by Prof. Rudolf Rabenstein. The two courses complement each other, but can also be taken separately.
Aspects related to music processing are covered in the following lectures:
Textbook:
Meinard Müller
Information Retrieval for Music and Motion
ISBN: 978-3-540-74047-6,
Springer
Reading assignment: Chapter 1
Reading assignment: Section 2.1 of Chapter 2
Exercises 1.1 to Exercises 1.12 of Chapter 1.
Exercises 2.1 to Exercises 2.8 of Chapter 2. The reading assignments and exercises are due to 10.11.2014. Each group has to hand in a handwritten solution of all exercises in the meeting on 10.11.2014 from 14:15 to 16:00 (before the lecture, same room). Please be prepared to ask questions in this meeting about the lecture and the exercises.
Practical exercises (ZIP) Responsible for the practical exercises is Jonathan Driedger.
The practical exercises are due to 04.12.2014. Each group has to hand in solutions and MATLAB implementations of the exercises, which are to be presented in the meeting on 08.12.2014 from 14:15 to 16:00 (before the lecture, same room). For questions please contact Jonathan Driedger.
Reading assignment (selected book chapter): Book
Each group has to hand in a summary of the assigned book chapter as a PDF until 12.01.2015.
Please send the PDF via e-mail to Prof. Dr. Meinard Müller and
Jonathan Driedger.
Latex sources for the summary's template (with additional explanations) can be found here: ZIP