Audio content feature selection and classification : a random forests and decision tree approach
(2015)
Presentation / Conference
AI-Maathidi, M., & Li, F. (2015, December). Audio content feature selection and classification : a random forests and decision tree approach. Presented at IEEE International Conference on Progress in Informatics and Computing (PIC), Nanjing, China
Content information can be extracted from soundtracks of multimedia files. A good audio classifier as a preprocessor
is crucial in such applications. Efforts have been made
to develop effective and efficient audio content classifiers in
which feat...
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