| Paper: | AE-P4.1 | ||
| Session: | Applications to Music | ||
| Time: | Thursday, May 18, 16:30 - 18:30 | ||
| Presentation: | Poster | ||
| Topic: | Audio and Electroacoustics: Applications to Music | ||
| Title: | MUSICAL GENRE CLASSIFICATION VIA GENERALIZED GAUSSIAN AND ALPHA-STABLE MODELING | ||
| Authors: | Christos Tzagkarakis, Athanasios Mouchtaris, Panagiotis Tsakalides, University of Crete / ICS-FORTH, Greece | ||
| Abstract: | This paper describes a novel methodology for automatic musical genre classification based on a feature extraction /statistical similarity measurement approach. First, we perform a 1-D wavelet decomposition of the music signal and we model the resulting subband coefficients using the Generalized Gaussian Density (GGD) and the Alpha-Stable distribution. Subsequently, the GGD and Alpha-Stable distribution parameters are estimated during the feature extraction step, while the similarity between two music signals is measured by employing the Kullback-Leibler Divergence (KLD) between their corresponding estimated wavelet distributions. We evaluate the performance of the proposed methodology by using a dataset consisting of six different musical genre sets. | ||
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