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Music Emotion Detection Using Hierarchical Sparse Kernel Machines
- Source :
- The Scientific World Journal, Vol 2014 (2014), The Scientific World Journal
- Publication Year :
- 2014
- Publisher :
- Hindawi Limited, 2014.
-
Abstract
- For music emotion detection, this paper presents a music emotion verification system based on hierarchical sparse kernel machines. With the proposed system, we intend to verify if a music clip possesses happiness emotion or not. There are two levels in the hierarchical sparse kernel machines. In the first level, a set of acoustical features are extracted, and principle component analysis (PCA) is implemented to reduce the dimension. The acoustical features are utilized to generate the first-level decision vector, which is a vector with each element being a significant value of an emotion. The significant values of eight main emotional classes are utilized in this paper. To calculate the significant value of an emotion, we construct its 2-class SVM with calm emotion as the global (non-target) side of the SVM. The probability distributions of the adopted acoustical features are calculated and the probability product kernel is applied in the first-level SVMs to obtain first-level decision vector feature. In the second level of the hierarchical system, we merely construct a 2-class relevance vector machine (RVM) with happiness as the target side and other emotions as the background side of the RVM. The first-level decision vector is used as the feature with conventional radial basis function kernel. The happiness verification threshold is built on the probability value. In the experimental results, the detection error tradeoff (DET) curve shows that the proposed system has a good performance on verifying if a music clip reveals happiness emotion.
- Subjects :
- Sound Spectrography
Support Vector Machine
Article Subject
Computer science
Emotions
lcsh:Medicine
Machine learning
computer.software_genre
lcsh:Technology
General Biochemistry, Genetics and Molecular Biology
Pattern Recognition, Automated
Relevance vector machine
Dimension (vector space)
Biomimetics
Feature (machine learning)
Humans
Hierarchical control system
lcsh:Science
General Environmental Science
lcsh:T
business.industry
lcsh:R
General Medicine
Support vector machine
Computer Science::Sound
Kernel (statistics)
Radial basis function kernel
Auditory Perception
Probability distribution
lcsh:Q
Artificial intelligence
business
computer
Algorithms
Music
Research Article
Subjects
Details
- ISSN :
- 1537744X and 23566140
- Volume :
- 2014
- Database :
- OpenAIRE
- Journal :
- The Scientific World Journal
- Accession number :
- edsair.doi.dedup.....c6f3a16756e92d51aa1851a1e8076e52