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.