Robust Multiplicative Audio and Speech Watermarking Using Statistical Modeling
Robust Multiplicative Audio and Speech Watermarking Using Statistical Modeling
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DOI：
10.1109/icc.2009.5199424
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发表时间：
2009-06
期刊：
影响因子：
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通讯作者：
M. Akhaee;N. Kalantari;F. Marvasti
中科院分区：
文献类型：
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作者：
M. Akhaee;N. Kalantari;F. Marvasti
本文提出了一种针对音频和语音信号的半盲乘法水印方法。在接收端，设计并实现了基于信道侧信息的噪声环境下高斯信号和拉普拉斯信号的最优最大似然检测器。通过分析计算和仿真验证了该方案的性能。然后，我们将所提出的方案应用于语音和音频信号。为了提高鲁棒性，将该算法应用于主机信号的低频分量。此外，采用音频质量感知评价（PEAQ）和语音质量感知评价（PESQ）算法对水印的不可听性进行了精细控制。在多个音频和语音信号上的实验结果表明，与最近的一种水印方案相比，该技术具有更高的鲁棒性。
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 channel side 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 a recent watermarking scheme.