Constructing robust categorical and typological classifiers, i.e., finding auditory constructs utilized for describing music categories, is an important problem in music genre classification. Supervised methods such as support vector machine (SVM) achieve state of the art performance for genre classification but suffer from over-fitting on training examples. In this paper, we introduce a superv...

II. REVIEW OF STATE OF THE ART Abstract—Classification of musical genres gives a useful measure of similarity and is often the most useful descriptor of a musical piece. Principal Component Analysis (PCA) has been generally applied on raw music signals to capture the major components for each genre. As a large number of principal components are obtained for different genres, the purpose of appl...

The introduction of digital music representation considerably altered the ways of creating, accessing and using music. Until today an immense number of music archives has been made available so that the actual attitude of music consumption has changed fundamentally. Both the commercial domain as for instance represented by music producers or music distributors and the private domain play a majo...

Aesthetic perception of music has been extensively researched in the last decades. Numerous studies suggest that listeners find a piece of music more or less pleasant according to its complexity. Experimental results show that complexity and liking have different relationship according to the musical genre examined, and that these two variables are also affected by other factors such as familia...

We describe a novel query-by-example (QBE) approach in music information retrieval that allows a user to customize query examples by directly modifying the volume of different instrument parts. The underlying hypothesis of this approach is that the musical mood of retrieved results changes in relation to the volume balance of different instruments. On the basis of this hypothesis, we aim to cla...

We here summarize our experience running a challenge with open data for musical genre recognition. Those notes motivate the task and the challenge design, show some statistics about the submissions, and present the results.

In this publication we describe a novel two-dimensional approach for automatic music genre classification. Although the subject poses a well studied task in Music Information Retrieval, some fundamental issues of genre classification have not been covered so far. Especially many modern genres are influenced by manifold musical styles. Most of all, this holds true for the broad category “World M...