School of Electronic Engineering and Computer Science

C4DM Seminar: Harald Groghanz on “Music Structure Analysis: Paths like Blocks”

3 July 2014

Time: 2:00 - 3:00pm
Venue: Maths 103

Harald Groghanz of Bonn University will give a seminar entitled "Music Structure Analysis: Paths like Blocks". This C4DM Seminar will take place in Room 103 of the Mathematical Sciences Building at Queen Mary University of London, Mile End Road, London E1 4NS.

Title: Music Structure Analysis: Paths like Blocks

Abstract: In music structure analysis the two principles of repetition and homogeneity are fundamental for partitioning a given audio recording into musically meaningful structural elements. When converting the audio recording into a suitable self-similarity matrix (SSM), repetitions typically lead to path structures, whereas homogeneous regions yield block structures. In previous research, handling both structural elements at the same time has turned out to be a challenging task.

In this talk, I will show that paths and blocks may like each other. After giving an illustrative introduction to various segmentation principles, I will present an idea for converting path structures into block structures. The main technical step consists in an eigenvalue decomposition of an SSM in combination with suitable clustering techniques. I will discuss the theoretical background by considering typical examples. Then, I demonstrate the effectiveness of the proposed conversion procedure by showing that algorithms previously designed for homogeneity-based structure analysis can now be applied for repetition-based structure analysis.

Bio: Harald Grohganz recieved the M.Sc. (Diplom) degree in mathematics from Bonn University in 2010. Since October 2010, he is pursuing a Ph.D. in the Multimedia Information Retrieval and Signal Processing group at Bonn University under the joint supervision of Michael Clausen (Bonn University) and Meinard Müller (International Audio Laboratories Erlangen). Working in the field of music signal processing and music information retrieval, his research interests cover music structure analysis, music segmentation, key and timbre estimation, rhythm transcription, and user interface design.