Drawbacks of existing segmentation, classification and feature extraction approaches

Merits of our proposed work

・ It can be applied only on discrete audio segments.

・ Generation of extra overhead during the computation of MFCC features.

・ Distinguishing of the speech from the music signals is poor.

・ The accuracy of the existing classification techniques is low.

・ High computational complexity and cost.

・ The clear features of the speech signal filtered from other background signals are obtained.

・ PNN-based classification provides a better prediction of the classified label using the probability estimation.

・ The presence of silence and irrelevant frequency details in the audio signal is eliminated.

・ PNN classification approach achieves efficient classification of the musical and non-musical signal.

・ The accuracy of the proposed approach is high.