Distortion based Watermark Extraction Technique Using 1D CNN

We have proposed a novel concept of a digital watermarking technique for music data that focuses on the use (a) of sound synthesis and sound effect techniques. The previous proposed technique was confirmed a vulnerability to high-pass filtering. This paper describes the details of the conventional embedding technique and the improved traction technique that employs the Deep Neural Networks. This paper describes the experimental results of evaluating the resistance of the proposed technique against high-pass filtering. It is demonstrated that the proposed technique in this paper has appropriate resistance (b) against high-pass filtering attack, which was not good at conventional technique.