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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 한국정보처리학회 JIPS(Journal of Information Processing Systems) JIPS(Journal of Information Processing Systems) 제13권 제2호
- 발행연도
- 2017.1
- 수록면
- 400 - 416 (17page)
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초록· 키워드
오류제보하기
Music emotion is an important component in the field of music information retrieval and computational musicology. This paper proposes an approach for automatic emotion classification, based on rough set (RS) theory. In the proposed approach, four different sets of music features are extracted, representing dynamics, rhythm, spectral, and harmony. From the features, five different statistical parameters are considered as attributes, including up to the 4th order central moments of each feature, and covariance components of mutual ones. The large number of attributes is controlled by RS-based approach, in which superfluous features are removed, to obtain indispensable ones. In addition, RS-based approach makes it possible to visualize which attributes play a significant role in the generated rules, and also determine the strength of each rule for classification. The experiments have been performed to find out which audio features and which of the different statistical parameters derived from them are important for emotion classification. Also, the resulting indispensable attributes and the usefulness of covariance components have been discussed. The overall classification accuracy with all statistical parameters has recorded comparatively better than currently existing methods on a pair of datasets.
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참고문헌 (25)
참고문헌 신청
/ / MOODetector
/ / ROSE2 (Rough Sets Data Explorer)
/ / Soundtracks datasets for music and emotion
A. J. Smola / 2004 / A tutorial on support vector regression / Statistics and Computing 14 (3) : 199 ~ 222
A. Papoulis / 2002 / Pillai, Probability, Random Variables, and Stochastic Processes / McGraw-Hill
/ / ROSE2 (Rough Sets Data Explorer)
/ / Soundtracks datasets for music and emotion
A. J. Smola / 2004 / A tutorial on support vector regression / Statistics and Computing 14 (3) : 199 ~ 222
A. Papoulis / 2002 / Pillai, Probability, Random Variables, and Stochastic Processes / McGraw-Hill
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