An efficient speech perceptual hashing authentication algorithm based on the linear prediction minimum mean squared error

被引：0
|
作者：
Zhang Q. [1 ]
Hu W. [1 ]
Qiao S. [1 ]
Zhang T. [1 ]
机构：
[1] School of Computer and Communication, Lanzhou University of Technology, Lanzhou
来源：
| 1600年 / Huazhong University of Science and Technology卷 / 44期
关键词：
Linear prediction-minimum mean squared error (LP-MMSE); Perception of robustness; Perceptual hashing; Spectral entropy; Speech authentication;
D O I：
10.13245/j.hust.161222
中图分类号：
学科分类号：
摘要：
In order to meet robustness and discrimination of content preserving operations in mobile speech communication, and the need for high-efficiency certification and other requirements, a novel efficient speech perceptual hashing authentication algorithm based on the linear prediction-minimum mean squared error (LP-MMSE) was proposed. Firstly, the algorithm conducted linear prediction coding (LPC) on speech signal after pre-processing, framing and windowing to obtain the minimum mean squared error (MMSE) coefficient matrix. Secondly, spectral entropy parameter matrix of each frame was calculated through the spectral entropy method. Finally, binary perceptual hash sequence was generated through combining these two matrixes above. Experimental results show that the proposed algorithm is better than other existing algorithms in terms of compactness, and has a good robustness, discrimination against content preserving operations. It also has high authentication efficiency and can meet the requirements of real-time speech authentication. © 2016, Editorial Board of Journal of Huazhong University of Science and Technology. All right reserved.
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页码：127 / 132
页数：5
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