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Low-rate speech coding Research and Implementation of Information Hiding

Author: XiaoBo
Tutor: HuangYongFeng
School: Tsinghua University
Course: Information and Communication Engineering
Keywords: Complementary neighbor vertex algorithm Low-rate speech coding Information Hiding Vector quantization Codebook partition
CLC: TN912.3
Type: Master's thesis
Year: 2009
Downloads: 38
Quote: 2
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Abstract


Low-rate speech coding information hiding problem is the difficulty of the field of information hiding, but also to build a communication system based on information hiding. By modifying the encoding vector quantization is one of the main sectors to achieve embedding method in which the grouping is reasonable code determines the merits of concealment of information hiding. This article is based QIM methods and graph theory, proposed grouping algorithm optimized codebook, namely complementarity neighbor vertex algorithm (CNV). The algorithm for any given codebook can guarantee divide the result that each codeword and its nearest neighbor codewords belong to different groups, and making additional quantization distortion of local maxima obtained for various dividing its minimal . On the theoretical side, the paper first modeling graph theory to prove the above two conclusions. Next, the counter example analysis of the constraint that each code word and its nearest neighbor vertices of two or three twenty-two packets belonging to different groupings of any common codebook is not established. In order to analyze the existence of a given grouping grouping satisfy the above conditions, we propose a method based on backtracking search. In addition, reuse CNV proposed algorithm results divided into two groups each for once again, to obtain an approximate four groups optimization method to improve the capacity of information hiding. In actual coding, we use the CNV algorithm iLBC, G.729, G.723.1 three coding LPC coefficients vector quantization codebook do division, gives the results of the group and made the discussion. Backtracking search results show not in accordance with the above code similar to the constraints of CNV in multiple groups, but approximate optimization methods can be divided into four groups well established. Through a lot of experiments and found that CNV algorithm quantization error is less than the average divided randomly divided, and are conducive to achieving a smaller maximum quantization error. The actual information used in the hidden partition on the subjective evaluation of speech quality can not distinguish between subjective experience shows that the confidential information embedded in the synthesized speech and the synthesized speech in common. Using the average LPC cepstrum distortion as an objective evaluation criteria and found that CNV division algorithm has better voice quality, and divided into four groups approximation method works better than a direct replacement for quantitative results of this class method. Finally, the method is applied to the preliminary work CNV VoIP-based communication system, information hiding, by the practical application of its validity, the transmission rate and the theoretical analysis, to meet the needs of practical application, is an ideal hiding method.

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CLC: > Industrial Technology > Radio electronics, telecommunications technology > Communicate > Electro-acoustic technology and speech signal processing > Speech Signal Processing
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