An Approach to Information Hiding in Low Bit-Rate Speech Stream

Abstract

In this paper we introduce a novel codebook partition algorithm for quantization index modulation (QIM), which is applied to information hiding in instant low bit-rate speech stream. The QIM method divides the codebook into two parts, each representing '0' and '1' respectively. Instead of randomly partitioning the codebook, the relationship between codewords is considered. The proposed algorithm - complementary neighbor vertices (CNV) guarantees that every codeword is in the opposite part to its nearest neighbor, and the distortion is limited by a bound. The feasibility of CNV is proved with graph theory. Moreover, in our work the secret message is embedded in the field of vector quantization index of LPC coefficients, getting the benefit that the distortion due to QIM is lightened adaptively by the rest of the encoding procedure. Experiments on iLBC and G.723.1 verify the effectiveness of the proposed method. Both objective and subjective assessments show the proposed method only slightly decreases the speech quality to an indistinguishable degree. The hiding capacity is no less than 100 bps. To the best of our knowledge, this is the first work adopting graph theory to improve the codebook partition while using QIM in low bit-rate streaming media.