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Speech authentication by semi-fragile speech watermarking utilizing analysis by synthesis and spectral distortion optimization

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Abstract

This paper proposes an improved semi-fragile speech watermarking scheme by quantization of linear prediction (LP) parameters, i.e., the inverse sine (IS) parameters. The spectral distortion due to watermark embedding is controlled to meet the ‘transparency’ criterion in speech coding. A modified bit allocation algorithm combined with watermarking is developed to determine the quantization step so that the ‘transparency’ requirement is satisfied. Due to the statistical nature, the LP coefficients estimated from the watermarked speech signal are different from the watermarked LP coefficients even in the absence of attacks. This effect is the cause of increase in decoding error and minimum authentication length. To tackle this problem, an Analysis by Synthesis (AbS) scheme is developed to reduce the difference between the estimated LP coefficients and the watermarked ones. The watermark detection threshold and minimum authentication length are then derived according to the probability of error and the signal to noise ratio (SNR) requirements. Experimental results show that the proposed AbS based method can effectively reduce the difference between the watermarked IS parameter and the extracted IS parameter when there is no attacks. In addition, the modified bit allocation algorithm can automatically find the appropriate quantization step used in the odd-even modulation so that the transparency requirement is satisfied.

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Acknowledgements

This work is supported by research project of ”SUST Spring Bud” under the grant number: 2009AZZ155. The work of the second author is also supported by the project of National Natural Science Foundation of China (NSFC) under project grant number: 61071087. The authors would like to thank the anonymous reviewers for their constructive comments and suggestions. We are indebted to the reviewers for their valuable time spent on the manuscript of this paper. The first author would like to thank Prof. Zhe-Ming Lu, Prof. Sheng-He Sun, Prof. Jeng-Shyang Pan and Prof. Xia-Mu Niu for their guidance and help in developing the basic algorithm upon which the extension in this paper is built.

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Correspondence to Bin Yan.

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Yan, B., Guo, YJ. Speech authentication by semi-fragile speech watermarking utilizing analysis by synthesis and spectral distortion optimization. Multimed Tools Appl 67, 383–405 (2013). https://doi.org/10.1007/s11042-011-0861-7

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