科研之友
微信
新浪微博
Facebook
分享链接
摘要
Combined with the linear prediction-minimum mean squared error (LP-MMSE), an efficient perceptual hashing algorithm based on improved spectral entropy for speech authentication was proposed in this paper. The linear prediction analysis is conducted on speech signal after preprocessing, framing and adding windows, and obtained the minimum mean squared error coefficient matrix. And then, the spectral entropy parameter matrix of each frame is calculated by using improved spectral entropy method. And the final binary perceptual hashing sequence is generated based on the above two matrices, and the speech authentication is completed. Comparing the experimental results of combining the Teager energy operator (TEO) with the linear predictive coefficients (LPC), LP-MMSE and line spectrum pair (LSP) coefficient respectively, it can be seen that the proposed algorithm had a good compromise between robustness, discrimination and authentication efficiency, and the proposed algorithm can meet the requirement of real-time speech authentication in speech communication. Experimental results show that the proposed algorithm was better than other existing methods in compactness.
