Title :
Hierarchical Genre Classification for Large Music Collections
Author :
Brecheisen, Stefan ; Kriegel, Hans-Peter ; Kunath, Peter ; Pryakhin, Alexey
Author_Institution :
Inst. of Informatics, Univ. of Munich
Abstract :
The rapid progress in digital music distribution has lead to the creation of large collections of music. There is a need for content-based music classification methods to organize these collections automatically using a given genre taxonomy. To provide a versatile description of the music content, several kinds of features like rhythm, pitch or timbre characteristics are commonly used. Taking the highly dynamic nature of music into account, each of these features should be calculated up to several hundreds of times per second. Thus, a piece of music is represented by a complex object given by several large sets of feature vectors. In this paper, we propose a novel approach for the hierarchical classification of music pieces into a genre taxonomy. Our approach is able to handle multiple characteristics of music content and achieves a high classification accuracy efficiently, as shown in our experiments performed on a real world data set
Keywords :
feature extraction; music; signal classification; digital music distribution; feature vector; hierarchical genre classification; music content; pitch characteristics; rhythm; timbre characteristics; versatile description; Classification tree analysis; Feature extraction; Histograms; Kernel; Large-scale systems; Multimedia databases; Music; Rhythm; Taxonomy; Timbre;
Conference_Titel :
Multimedia and Expo, 2006 IEEE International Conference on
Conference_Location :
Toronto, Ont.
Print_ISBN :
1-4244-0366-7
Electronic_ISBN :
1-4244-0367-7
DOI :
10.1109/ICME.2006.262797