Perceptual Hashing Algorithm For Speech Content Identification Based On Spectrum Entropy In Compressed Domain

[1]F. Karray, M. Alemzadeh, J. A. Saleh and M. N. Arab, “Human-Computer Interaction: Overview on State of the Art”, International Journal on Smart Sensing and Intelligent Systems, Vol. 1, No. 1, pp. 137-159, 2008.10.21307/ijssis-2017-283 Search in Google Scholar

[2]X. Niu and Y. Jiao, “ An overview of perceptual hashing”, Acta Electronica Sinica, Vol. 36, No. 7, pp. 1405-1411, 2008. Search in Google Scholar

[3]N. K. Verma, R. K. Sevakula, J. K. Gupta, S. Singh, S. Dixit and A. Salour, “Smartphone Application for Fault Recognition”, International Journal on Smart Sensing and Intelligent Systems, Vol. 6, No. 4, pp. 1763-1782, 2013. Search in Google Scholar

[4]J. Haitsma, T.Kalker and J. Oostveen, “Robust Audio Hashing for Content Identification”, International Workshop on Content-Based Multimedia Indexing, Vol. 4, pp. 117-124, 2001. Search in Google Scholar

[5]G. Grutzek, J. Strobl, B. Mainka, F. Kurth, C. Porschmann and H. Knospe, “Perceptual hashing for the identification of telephone speech”, Speech Communication; 10.ITG Symposium, Proceedings of.VDE, Germany, 2012, pp.1-4. Search in Google Scholar

[6]Y. Jiao, L. Ji and X. Niu, “Robust speech hashing for content authentication”, IEEE Signal Processing Letters, Signal Processing Letters, IEEE, Vol. 16, No. 9, pp. 818-821, 2009.10.1109/LSP.2009.2025827 Search in Google Scholar

[7]J. Gu, L. Guo, H. Liang and L. Cheng, “Effective robust speech authentication algorithm based on perceptual characteristics”, Journal of Chinese Computer Systems, Vol. 7, pp. 14611466, 2010. Search in Google Scholar

[8]L. Ghouti and A. Bouridane, “A robust perceptual audio hashing using balanced multiwavelets”, in Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing(ICASSP’06), France, 2006, pp. 209-212. Search in Google Scholar

[9]R. Lancini, F. Mapelli and R. Pezzano, “Audio content identification by using perceptual hashing”, in Proceedings of IEEE International Conference on Multimedia and Expo(ICME’04), Taipei, 2004, pp. 739-742. Search in Google Scholar

[10]P. J. O. Doets, M. M. Gisbert and R. L. Lagendijk, “On the comparison of audio fingerprints for extracting quality parameters of compressed audio”, Electronic Imaging 2006, International Society for Optics and Photonics, 2006, pp. 60720L-60720L-12.10.1117/12.642968 Search in Google Scholar

[11]M. Li, “MDCT-based compressed domain perceptual audio hashing”, Harbin, Harbin institute of technology, 2008. Search in Google Scholar

[12]Y. Jiao, “Research on perceptual audio hashing”, Harbin, Harbin institute of technology, 2009. Search in Google Scholar

[13]P. Noll, “ MPEG digital audio coding”, IEEE Signal Processing Magazine, Vol. 14, No. 5, pp. 59-81, 1997.10.1109/79.618009 Search in Google Scholar

[14]L. Chang, X. Yu, W. Wan, C. Li and X. Xu, “Research and realization of speech segmentation in MP3 compressed domain”, Jounal of Computer Applications, Vol. 29, No. 4, pp. 1188-1192, 2009. Search in Google Scholar

[15]Y. Wang, L. Yaroslavsky and M. Vilermo, “On the relationship between MDCT, SDFT and DFT”, in Proceedings of the 5th International Conference on Signal Processing, Beijing, 2000, pp. 44-47. Search in Google Scholar

[16]Y. Liang, C. Bao, B. Xia, Y. He, X. Zhou and N.Li, “Compressed domain speech enhancement based on Gaussian mixture model”, Acta Electronica Sinica, Vol. 40, No. 10, pp. 2031-2038, 2012. Search in Google Scholar

[17]H. Misra, S. Ikbal, H. Bourlard and H. Hermansky, “Spectral entropy based feature for robust ASR”, in Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing(ICASSP’04), Canada, 2004, pp. I-193-6. Search in Google Scholar

[18]Y. Liu, W. Li, X. Li, Z. Wang and R. Feng, “A robust compressed-domain music fingerprinting technique based on MDCT spectral entropy”, Acta Electronica Sinica, Vol. 38, No. 5, pp. 1172-117, 2010. Search in Google Scholar

[19]Underbit Technologies, Inc, “MAD: MPEG Audio Decoder, http://www.underbit.com/products/mad”, 2013. Search in Google Scholar

[20]J. Haitsma and T. Kalker, “A Highly Robust Audio Fingerprinting System”, in Proceedings of International Symposium on Music Information Retrieval (ISMIR ‘02), Paris, 2002, pp. 107 – 115. Search in Google Scholar