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A security watermark scheme used for digital speech forensics

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Abstract

Based on digital watermark, a speech forensics scheme is proposed. The feature coefficients cross-correlation degree of speech signal is defined, and the property is discussed, which demonstrates that the feature is very robust. Then a new watermark embedding method based on the feature is explored, aiming to enlarge the embedding capacity and solve the security issue of watermark schemes based on public features. In this paper, for each fame of speech signal, it is cut into two parts, and each part is divided into some segments. Then frame number is mapped to a sequence of integers, which are embedded into the segments. The integers can be extracted used for forensics and tamper location after watermarked signal being attacked. Theoretical analysis and experimental results show that the scheme proposed is inaudible and robust against desynchronization attacks, enhances the security of watermark system and has a good ability for speech forensics.

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Acknowledgments

This paper is supported by the National Natural Science Foundation of China (Grant No. 61332012, 61272465, 61502409), Shenzhen R&D Program (GJHZ20140418191518323), Nanhu Scholars Program for Young Scholars of XYNU. We would like to thank the anonymous reviewers for their constructive suggestions.

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Authors and Affiliations

  1. College of Information Engineering and Shenzhen Key Laboratory of Media Security, Shenzhen University, Shenzhen, 518060, China

    Zhenghui Liu & Jiwu Huang

  2. College of Computer and Information Technology, Xinyang Normal University, Xinyang, 464000, China

    Zhenghui Liu & Chuanda Qi

  3. School of Computer & Software, Nanjing University of Information Science & Technology, Nanjing, 210044, China

    Xingming Sun

Authors
  1. Zhenghui Liu
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  2. Jiwu Huang
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  3. Xingming Sun
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  4. Chuanda Qi
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Correspondence to Zhenghui Liu.

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Liu, Z., Huang, J., Sun, X. et al. A security watermark scheme used for digital speech forensics. Multimed Tools Appl 76, 9297–9317 (2017). https://doi.org/10.1007/s11042-016-3533-9

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  • DOI: https://doi.org/10.1007/s11042-016-3533-9

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