Digital Speech Watermarking Based on Linear Predictive Analysis and Singular Value Decomposition

Nematollahi, Mohammad Ali; Vorakulpipat, Chalee; Gamboa-Rosales, Hamurabi; Ruiz, Francisco Javier Martínez; Vargas, José Ismael De la Rosa

doi:10.1007/s40010-017-0371-8

Cited by 6 publications

(12 citation statements)

References 21 publications

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“…In this section, we implement the methods in [20], [22], [25], [26], to compare the performance with the proposed method. These methods cover the representative methods for speech steganography: SS, RDM, SVD algorithms.…”

Section: Methodsmentioning

confidence: 99%

“…Through our experiments and analysis, we set f l = 1.5 kHz, f h = 2.5 kHz, α 1 = α 2 = 0.2. To ensure fairness in the evaluation of performance, the embedding rates of methods in [22], [25], [26] and the proposed method are identical at 25 bps, while the embedding rate of method in [20] is 12.5 bps for facilitating the use of spread spectrum in steganography. And we compare the performance from the imperceptibility, robustness, and security.…”

Section: Methodsmentioning

confidence: 99%

“…Table 2 shows the BER of five steganographic methods after these different attacks. Methods in [22], [25] and [26] provide little resistance to HPF attack. Method in [25] and method in [26] fail severely in the amplitude scaling attack, which are based on SVD-LSB and SVD-QIM technique respectively.…”

Section: B Robustnessmentioning

confidence: 99%

“…Methods in [22], [25] and [26] provide little resistance to HPF attack. Method in [25] and method in [26] fail severely in the amplitude scaling attack, which are based on SVD-LSB and SVD-QIM technique respectively. Although method in [22] can improve the robustness to the amplitude attack by using RDM, but it is still inferior to our method while embedding data into the non-voiced, salient frames in the speech signal.…”

Section: B Robustnessmentioning

confidence: 99%

“…Dhar and Shimamura [25] propose a DCT-SVDbased scheme using entropy and log-polar transformation (LPT), and data is embedded by quantizing the Cartesian component of highest singular value obtained from the DCT sub band with highest entropy value. Nematollah et al [26] design a scheme which utilizes linear predictive analysis (LPA) with SVD and QIM by applying the ability of LPA for modeling quasi-stationary part of the signal. Although the imperceptibility is improved, these SVD-based steganographic methods are still not robust enough to amplitude scaling attack.…”

Section: Introductionmentioning

confidence: 99%

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Robust Speech Steganography Using Differential SVD

et al. 2019

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The speech signal is different from the typical audio in terms of spectral bandwidth, intensity distribution, and signal continuity, thus how to achieve high imperceptibility and strong robustness for speech steganography is a big challenge. In this paper, we present a speech steganography scheme based on the parity-segmented method and the differential singular value decomposition (SVD). The selected discrete cosine transform (DCT) coefficients are divided into two segments according to parity order. In this way, the energy of the paired segments is approximately equal, therefore the changes in the singular values caused by data embedding are reduced, and high imperceptibility is achieved. Unlike the common SVD-based steganography, the differential SVD scheme can effectively remove the impact of amplitude scaling attack by embedding the secret message into the difference between the singular values. Experimental results show that the proposed method achieves high imperceptibility and strong robustness while resisting the state-of-the-art steganalytic methods. INDEX TERMS Steganography, differential SVD, paired segments, imperceptibility, amplitude scaling.

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