Abstract:
The explanation of how a decision made is
important for accepting the machine learning
technology, especially for applications such as
multimedia. SVMs have shown strong generalization
ability in a number of application areas, including
audio classification. However, the poor
comprehensibility hinders the success of the SVM for
audio class prediction. On the other hand, a decision
tree has good comprehensibility. This approach
combines the SVM with decision tree. We use the
SVM as a decision of binary tree to select strong
instances to generate rules; it is known as decision
SVM (DSVM). We considered eight audio classes:
silence, non-silence, speech with music, speech with
noise, music with environment sound, instrumental
music, environmental sound and noise. This
classification and analysis is intended to analyze the
structure of the sports video.
