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Audio Watermarking Based on HAS and Neural Networks in DCT Domain


We propose a new intelligent audio watermarking method based on the characteristics of the HAS and the techniques of neural networks in the DCT domain. The method makes the watermark imperceptible by using the audio masking characteristics of the HAS. Moreover, the method exploits a neural network for memorizing the relationships between the original audio signals and the watermarked audio signals. Therefore, the method is capable of extracting watermarks without original audio signals. Finally, the experimental results are also included to illustrate that the method significantly possesses robustness to be immune against common attacks for the copyright protection of digital audio.

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Correspondence to Hung-Hsu Tsai.

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Tsai, HH., Cheng, JS. & Yu, PT. Audio Watermarking Based on HAS and Neural Networks in DCT Domain. EURASIP J. Adv. Signal Process. 2003, 764030 (2003).

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