@Article{JICS-1-115, author = {}, title = {Hierarchical Support Vector Machines for Audio Classification}, journal = {Journal of Information and Computing Science}, year = {2006}, 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 = {3080-180X}, doi = {https://doi.org/}, url = {http://global-sci.org/intro/article_detail/jics/22851.html} }