Title :
Feature selection method for music mood score detection
Author :
Miyoshi, Masato ; Tsuge, Satoru ; Oyama, Tadahiro ; Ito, Momoyo ; Fukumi, Minoru
Author_Institution :
Univ. of Tokushima, Tokushima, Japan
Abstract :
In general, music retrieval and classification methods using music moods use a lot of acoustic features similar to music genre classification. These features are used as the spectral features, the rhythm features, the harmony features, and so on. However, all of these features may not be efficient for music retrieval and classification using music moods. Hence, in this paper, we propose a feature selection method for detecting music mood scores. In the proposed method, features which have strong correlation with mood scores are selected from a lot of features. Then, these are input into Multi-Layer Neural Networks (MLNNs) and mood scores are detected every mood labels. For evaluating the proposed method, we conducted the music mood score detection experiments. Experimental results show that the proposed method improves the detection performance compared to not use the feature selection.
Keywords :
acoustic signal processing; information retrieval; music; neural nets; pattern classification; signal detection; acoustic features; feature selection method; multi-layer neural networks; music classification; music genre classification; music mood score detection; music retrieval; Accuracy; Brightness; Correlation; Feature extraction; Mood; Timbre; Feature extraction; Feature selection; Mood score detection; Music mood; Music retrieval and classification;
Conference_Titel :
Modeling, Simulation and Applied Optimization (ICMSAO), 2011 4th International Conference on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-1-4577-0003-3
DOI :
10.1109/ICMSAO.2011.5775562