Abstract:
This paper describes the work done on the
development of an audio classification system. Audio recordings
are classified into basic audio types such as speech or music.
Audio classification is processed in two parts, feature extraction
and classification, which makes it suitable for different
applications. In first part, input audio signal is transformed into
feature vectors, carrying characteristics information about the
signal. Audio Features for this task include Short Time Energy
(SE), Zero Crossing Rate (ZC) and Mel Frequency Cepstral
Coefficient (MFCC). The second part classify feature vector into
speech or music. Gaussian Mixture Model (GMM) is used for
classification task. The overall accuracy rate of this paper gets
around 93%.
