By Topic

Audio hash function based on non-negative matrix factorisation of mel-frequency cepstral coefficients

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $31
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Chen, N. ; Sch. of Commun. & Inf. Eng., Shanghai Univ., Shanghai, China ; Xiao, H.-D. ; Wan, W.

Robust audio hash function defines a feature vector that characterises the audio signal, independent of content preserving manipulations, such as MP3 compression, amplitude boosting/cutting, low-pass filtering etc. In this study, the authors propose a new audio hash function based on the non-negative matrix factorisation (NMF) of mel-frequency cepstral coefficients (MFCCs). Their work is motivated by the fact that the orthogonality constraints in the singular value decomposition (SVD) make the low-rank singular vectors of audio with distinct local difference be the same. Thus, the available hash function based on SVD of MFCCs cannot achieve satisfactory discrimination. Although the non-negative constraints of NMF result in the basis that captures the local feature of the audio, thereby significantly reducing misclassification. Experimental results over large audio databases demonstrate that the proposed scheme achieves better performances, in terms of perceptual robustness and discrimination, than the available SVD-MFCCs-based hash function.

Published in:

Information Security, IET  (Volume:5 ,  Issue: 1 )