2024-03-29T09:32:53Z
https://meral.edu.mm/oai
oai:meral.edu.mm:recid/3343
2021-12-13T05:51:36Z
1582963302567:1597824273898
user-ucsy
Acoustic Events Classification Using Support Vector Machines (SVMs)
Aung, Htat Htat
Oo, Hlaing Thida
In this paper, an approach is built toautomatically detect acoustic events that areproduced in a meeting or lecture room environment.Six audio classes are to be classified through thisapproach. The classes considered are music, speech,clapping, door slam, cough, and laughter. Severalevents samples are collected from the Internet.Support Vector Machines (SVMs) perform trainingand testing the events classification on perceptualand MFCC features set. A hierarchical clusteringscheme is used therefore the required number ofbinary SVM classifier is also reduced. The system istested on different data sets and its effectiveness isdetermined with classification accuracy on audioevent frames.
2010-12-16
http://hdl.handle.net/20.500.12678/0000003343
https://meral.edu.mm/records/3343