Visualized Feature Fusion and Style Evaluation for Musical Genre Analysis

Different kinds of features in time domain, spectral domain and cepstral domain are used for musical genre classification. In this paper, through the fusion of short-term timbral features and long-term rhythmic feature, we propose a novel method where: musical genre vector is constructed using the likelihood ratio of GMM (Gaussian Mixture Model) and radar chart is applied to provide visualized style evaluation for musical genre analysis, a promising performance is achieved over our database consisting of seven different types of music. Because of the fuzzy definition of musical genres, we also investigate the music with dual-genre based on musical genre vector and radar chart.