Abstract
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.
Highlights
The maturity of networking and data-compression techniques promotes an efficient distribution for digital products
Illegal reproduction and distribution of digital audio products become much easier by using the digital technology with lossless data duplication
The watermark technique could be applied to establish the ownership of digital audio for copyright protection and authentication
Summary
The maturity of networking and data-compression techniques promotes an efficient distribution for digital products. The techniques of conventional cryptography protect the content from anyone without private decrypted keys They are useful in protecting an audio from being intercepted during data transmission [1]. An audio watermarking method has been proposed in [4] to effectively protect the copyright of audio. Swanson’s method requires the original audio for the watermark extraction. This kind of watermarking methods fails to identify the owner copyright of audio due to the ambiguity of ownerships. On the basis of the characteristics of the human auditory system (HAS) and the techniques of neural networks, this paper presents a new audio watermarking method without the original audio for the watermark extraction.
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