Beta 1


Title Content Based Music Similarity Estimation
Author Rump, Halfdan
Troelsgård, Rasmus
Supervisor Hansen, Lars Kai (Intelligent Signal Processing, Department of Informatics and Mathematical Modeling, Technical University of Denmark, DTU, DK-2800 Kgs. Lyngby, Denmark)
Institution Technical University of Denmark, DTU, DK-2800 Kgs. Lyngby, Denmark
Thesis level Bachelor thesis
Year 2009
Abstract This Bachelor project is an attempt to investigate the requirements for creating a system capable of estimating similarity between music tracks. A change detection algorithm analyses each music track, and divides the tracks into segments re flecting the musical contents. The purpose of a dynamic segmentation scheme is that it should be possible to represent each segment by a single statistical model, capable of modelling temporal correlations. The algorithm used for segmenting the tracks is based on an algorithm developed for detecting speaker changes in news stream broadcasts. An attempt to optimise the algorithm for better performance with music was made. Furthermore an attempt to modify the structure of the algorithm in order to obtain better performance was made. A manually segmented training set was used to optimise the algorithms and measure performance. Each segment is represented by a Multivariate Autoregressive model, calculated on the MEL-scaled cepstral coefficients. Investigations of the usability of MAR for this particular application were carried out. System performance, evaluated as the ability to compare music on a segment basis, was measured on a data set of approximately 50 hours of music, divided into 11 genres.
Imprint Technical University of Denmark (DTU) : Kgs. Lyngby, Denmark
Series IMM-B.Sc.-2009-06
Fulltext
Original PDF bac09_06_net.pdf (1.13 MB)
Admin Creation date: 2009-06-16    Update date: 2010-08-25    Source: dtu    ID: 244730    Original MXD