A Comprehensive Study in Benchmarking Feature Selection and Classification Approaches for Traditional Malay Music Genre Classification
Source: Universiti Putra Malaysia
Machine learning techniques for automated musical genre classification are currently widely studied. With large collections of digital musical files, one approach to classification is to classify by musical genres such as pop, rock and classical in Western music. Beat, pitch and temporal related features are extracted from audio signals and various machine learning algorithms are applied for classification. Features that resulted in better classification accuracies for Traditional Malay Music (TMM), in comparison to western music, in a previous study were beat related features.