Blind Speech Watermarking Method with Frame Self-Synchronization Based on Spread-Spectrum Using Linear Prediction Residue  
[PERSON]  
1 School of Information Science, Japan Advanced Institute of Science and Technology, Ishikawa 923-1292, Japan; [EMAIL_ADDRESS] (S.K. ); [EMAIL_ADDRESS] (M.U.) [PERSON]  
1 School of Information Science, Japan Advanced Institute of Science and Technology, Ishikawa 923-1292, Japan; [EMAIL_ADDRESS] (S.K. ); [EMAIL_ADDRESS] (M.U.) 1 School of Information Science, Japan Advanced Institute of Science and Technology, Ishikawa 923-1292, Japan; [EMAIL_ADDRESS] (S.K. ); [EMAIL_ADDRESS] (  
occurred [1; 2]. Therefore, it is necessary to achieve secure protection and implement preventative countermeasures in speech communication technology. The speech watermarking technique has attracted attention as a solution to achieve these countermeasures against speech tampering and spoofing [3; 4]. This technique aims to protect digital speech content by embedding an inaudible security code into a speech signal and by detecting the embedded security code from the watermarked speech signal. In general, speech watermarking methods must meet four requirements to provide a useful and reliable form of audio/speech watermarking [2; 5]: (1) inaudibility (inaudible to humans with no sound distortion caused by the embedded data), (2) robustness (not affected when subjected to techniques such as data compression and malicious attacks), (3) blind-detectability (high possibility of detecting the embedded data without using the original or reference signal), and (4) confidentiality (secure and undetectable concealment of embedded data). Conventional audio watermarking techniques can also be used as speech watermarking [6]. Typical examples include the least-significant bit (LSB) replacement method [3] and the direct spread spectrum (DSS) method [3; 7]. The LSB method has an advantage concerning inaudibility because it has less effect on the magnitude [3] but a disadvantage regarding fragility against any modifications. In contrast, the DSS method has an advantage regarding robustness against various modifications [3; 7] but a disadvantage regarding inaudibility due to sound distortion by spectrum spreading. In short, the LSB method satisfies requirement (1) but not (2), and the DSS method satisfies requirement (2) but not (1). Other state-of-the-art audio watermarking methods include singular value decomposition (SVD) with dither modulation quantization, which is a type of quantization index modulation (QIM) [8; 9], and various phase modulation techniques [5; 10]. Although they have strong points in terms of one or two requirements (e.g., inaudibility and robustness or blind-detectability), they cannot satisfy all four requirements simultaneously due to fragility against speech codecs and sensitivity to frame desynchronization attacks. This suggests that a speech watermarking method using typical audio watermarking techniques must be reconsidered to satisfy the robustness against speech codecs and to ensure blind detection with frame synchronization. There are some specific speech watermarking methods that depend on speech codecs [2]. These methods are individually designed by adaptively embedding and detecting a security code into/from parameters (linear predictive parameters, codebook parameters, vector quantization, etc.) in the speech codec scheme for G.711, G.721, G.728, G.729, and GSM, although the main approach is taken into code excited linear prediction (CELP) and mixed excitation linear prediction (MELP). These methods can be used for covert communication based on the VoIP system and the design of real-time communication over PSTN [2]. All of these methods have some kind of trade-off between sound quality, capacity, and robustness.