Huang Yi-bo
College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou, Gansu, 730050, China
Zhang Qiu-yu
School of Computer and Communication, Lanzhou University of Technology, Lanzhou, Gansu, 730050, China
Yuan Zhan-ting
College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou, Gansu, 730050, China
ABSTRACT
While evaluating the performance of the speech perceptual hash algorithms, we need to test their robustness, safety and real-time properties, as well as judging the perceived similarity of the detected speeches. But the existing algorithms are so insensitive to slight speech tampering that the tampered speeches are mistakenly considered to be semantically unchanged. Therefore, we present an algorithm for measuring the perceived similarity. By displaying desirable sensitivity to slight speech tampering, the proposed algorithm can detect slight speech tampering and judge whether the meanings have changed. The proposed algorithm first divides the speech signals to many segments and then performs correlation coefficient test on each segment in order to compute the similarity. The experiment results show that the proposed algorithm can effectively detect quality changes of the speech signals and the similarity of the slightly tampered speeches. Its performance in evaluating perceived similarity is superior to the popular similarity evaluation algorithms.
PDF References
How to cite this article
Huang Yi-bo, Zhang Qiu-yu and Yuan Zhan-ting, 2013. Algorithm for Evaluating Speech Perceptual Hash Similarity after Slight Tampering Occurs. Information Technology Journal, 12: 3591-3595.
DOI: 10.3923/itj.2013.3591.3595
URL: https://scialert.net/abstract/?doi=itj.2013.3591.3595
DOI: 10.3923/itj.2013.3591.3595
URL: https://scialert.net/abstract/?doi=itj.2013.3591.3595
REFERENCES
- Chen, N. and W.G. Wan, 2009. Speech hashing algorithm based on short-time stability. Proceedings of the 19th International Conference on Artificial Neural Networks, September 14-17, 2009, Limassol, Cyprus, pp: 426-434.
CrossRef - Gupta, S., S. Cho and C.C.J. Kuo, 2012. Current developments and future trends in audio authentication. IEEE Multimedia, 19: 50-59.
CrossRefDirect Link - Jiao, Y.H., Q. Li and X.M. Niu, 2008. Compressed domain perceptual hashing for MELP coded speech. Proceedings of the International Conference on Intelligent Information Hiding and Multimedia Signal Processing, August 15-17, 2008, Harbin, Germany, pp: 410-413.
CrossRefDirect Link - Jiao, Y.H., L.P. Ji and X.M. Niu, 2010. Perceptual speech hashing and performance evaluation. Int. J. Innovative Comput. Inform. Control, 6: 1447-1458.
Direct Link - Jin, M. and C.D. Yoo, 2007. Temporal dynamics for spectral sub-band centroid audio fingerprints. Proceedings of the IEEE International Conference on Multimedia and Expo, July 2-5, 2007, Beijing, China, pp: 180-183.
CrossRef - Niu, X.M. and Y.H. Jiao, 2008. An overview of perceptual hashing. Acta Electron. Sin., 36: 1405-1411.
Direct Link