@Article{JICS-1-115, author = {}, title = {Hierarchical Support Vector Machines for Audio Classification}, journal = {Journal of Information and Computing Science}, year = {2024}, volume = {1}, number = {2}, pages = {115--118}, abstract = { Audio data is one of typical multimedia data and it contains plenty of information. Audio retrieval is becoming important content in multimedia information retrieval. In multimedia retrieval researches, it becomes more and more important research part how to construct better classifiers for audio classification and retrieval. Support Vector Machines, a novel method of the Pattern Recognition, presents excellent performance in solving the problems with small sample, nonlinear and local minima. But audio classification is a multi-class classification problem and it(cid:146)s just one of problems to be solved in SVM researches. In this paper, it compares several common Support Vector Machines and proposes a hierarchical Support Vector Machines based on audio features cluster method, combining audio features and hierarchical SVMS. It uses hierarchical classification method to classify audio data and it(cid:146)s proved better performance by experiments. }, issn = {1746-7659}, doi = {https://doi.org/}, url = {http://global-sci.org/intro/article_detail/jics/22851.html} }