Classification of three composers' popular songs using feature vectors based on the musical score information

概要

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This paper describes the extraction of features from three composers' songs and the classification of the songs by applying the NN rule with several feature vectors. The features are extracted from the score database that was built by inputting the musical score information. This research uses several 3-dimensional feature vectors that consist of the features of 5-note patterns, notes in a musical scale, intervals in a scale, and 3-note patterns in a scale. Each axis of the feature space represents the feature of each composer. The classification result indicates that the features of pitch transitions in a scale are more effective than those without a scale. This research also uses several 9-dimensional feature vectors that are the combinations of the features used in the 3-dimensional vectors. The classification result indicates that the combinations of the features of pitch transitions in a scale and those without a scale are effective. Next, this research examines the combinations of composers. The result shows that the correct classification ratio depends on the combination of composers. A prototype system to recommend songs has been made by applying the feature space studied in this research.