Audio Retrieval based on Cepstral Feature

The interest towards music is rapidly growing in our day to day life. It is necessary to have efficient system to retrieve relevant music for the user. The audio retrieval system mainly depends on the feature extraction process because only the meaningful feature will provide better retrieval task. In this work, audio information retrieval has been performed on GTZAN datasets using weighted Mel-Frequency Cepstral Coefficients (WMFCC) feature which is a kind of cepstral feature. The results obtained for the various stages of feature extraction WMFCC and retrieval performance plot has been presented. The mean precision values obtained for the audio files from the GTZAN database are 96.40% respectively. General Terms Segmentation, query, Audio, Filters.

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