Sound Source Classification using Support Vector Machine
This paper shows an application of a learning method for acoustic signal
classification by an auditory robot.
The learning approach provided unified classification method without
considering the characteristics of target signals.
Support Vector Machine was adopted to obtain the classifier and the
target signal was characterized by Mel-Scale Log Spectrum which is a
general form to symbolize acoustic signals.
Results of actual experiments to classify 4 class of acoustic signals
showed the validity of the method.