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Analytical Approach to MFCC Based Space-Saving Audio Fingerprinting System

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dc.contributor.author Htun, Myo Thet
dc.date.accessioned 2019-07-23T04:33:27Z
dc.date.available 2019-07-23T04:33:27Z
dc.date.issued 2019-02-27
dc.identifier.uri http://onlineresource.ucsy.edu.mm/handle/123456789/1218
dc.description.abstract Audio fingerprinting is a smart technology to identify music contents relevant to the query by comparing the content-based hash (fingerprint) of the query to known hashes in the fingerprint database. For a million-song library, size of the fingerprint database restricts speedy and correct music identification. In this paper, we present a space-saving audio fingerprinting system based on Mel Frequency Cepstral Coefficients and analyze in detail. For a number of cepstral coefficients with 12 as default, the system yields a 2712-bit fingerprint for a 3-sec audio clip, a significant reduction in storage compared to the 8192-bit fingerprint of well-known Philips Robust Hashing method. Experimental results also show that the more number of input value for cepstral coefficients, the larger the fingerprint size. The choice of Mel coefficients also affects the identification performance of the system: 8 to 12 coefficients gives the best similarity rates while preserving robustness of the fingerprints to signal distortion such as pitch shifting. en_US
dc.language.iso en en_US
dc.publisher Seventeenth International Conference on Computer Applications(ICCA 2019) en_US
dc.subject audio fingerprint en_US
dc.subject a million-song library en_US
dc.subject Mel Frequency Cepstral Coefficients en_US
dc.subject music identification en_US
dc.subject Philips Robust Hashing en_US
dc.title Analytical Approach to MFCC Based Space-Saving Audio Fingerprinting System en_US
dc.type Article en_US

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