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

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Abstract

In this paper different digital audio watermarking techniques have been proposed. Currently, more attention is given to combination of Discrete Wavelet Transform (DWT) and Singular Value Decomposition (SVD) techniques for watermarking purpose. Available DWT–SVD audio watermarking techniques cannot be applied to speech signals efficiently. However, Linear Predictive Analysis (LPA) technique can model digital speech signals (20–30 ms) in more flexible and efficient ways than DWT. In this paper, a novel digital speech watermarking technique is proposed by applying both LPA and SVD. Quantization Index Modulation (QIM) is further applied to embed the watermark bits. The experimental results show that not only time and memory were reduced significantly as compared to different DWT–SVD audio watermarking techniques, but also the proposed technique was more robust and imperceptible for speech watermarking than other DWT–SVD audio watermarking techniques.

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Authors and Affiliations

  1. Department of Computer Engineering, Islamic Azad University, Safadasht Branch, Tehran, Iran

    Mohammad Ali Nematollahi

  2. Cybersecurity Laboratory, Wireless Innovation and Security Research Unit, National Electronics and Computer Technology Center (NECTEC), 112 Phahonyothin Road, Khlong Nueng, Khlong Luang District, Pathumthani, 12120, Thailand

    Chalee Vorakulpipat

  3. Department of Electronics Engineering, Autonomous University of Zacatecas, 98000, Zacatecas, Zac., Mexico

    Hamurabi Gamboa-Rosales, Francisco J. Martinez-Ruiz & Jose I. De la Rosa-Vargas

Authors
  1. Mohammad Ali Nematollahi
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  2. Chalee Vorakulpipat
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  3. Hamurabi Gamboa-Rosales
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  4. Francisco J. Martinez-Ruiz
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  5. Jose I. De la Rosa-Vargas
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Correspondence to Mohammad Ali Nematollahi.

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Nematollahi, M.A., Vorakulpipat, C., Gamboa-Rosales, H. et al. Digital Speech Watermarking Based on Linear Predictive Analysis and Singular Value Decomposition. Proc. Natl. Acad. Sci., India, Sect. A Phys. Sci. 87, 433–446 (2017). https://doi.org/10.1007/s40010-017-0371-8

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  • DOI: https://doi.org/10.1007/s40010-017-0371-8

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