Robust audio and speech watermarking using Gaussian and Laplacian modeling

Authors:
Mohammad Ali Akhaee;Nima Khademi Kalantari;Farokh Marvasti
Affiliations:
Advanced Communications Research Institute (ACRI), Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran;Department of Electrical Engineering, AmirKabir University of Technology, Tehran, Iran;Advanced Communications Research Institute (ACRI), Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran
Venue:
Signal Processing
Year:
2010

Citing 13
Cited 2

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A norm-space, adaptive, and blind audio watermarking algorithm by discrete wavelet transform

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An overview of digital speech watermarking

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Abstract

In this paper, a semi-blind multiplicative watermarking approach for audio and speech signals has been presented. At the receiver end, the optimal maximum likelihood (ML) detector aided by the archived information for Gaussian and Laplacian signals in noisy environment is designed and implemented. The performance of the proposed scheme is analytically calculated and verified by simulation. Then, we adapt the proposed scheme to speech and audio signals. To improve robustness, the algorithm is applied to low frequency components of the host signal. Besides, the power of the watermark is controlled elegantly to have inaudibility using perceptual evaluation of audio quality (PEAQ) and perceptual evaluation of speech quality (PESQ) algorithms. Experimental results over several audio and speech signals show the higher robustness of the proposed technique in comparison with other watermarking schemes presented so far.