Design of audio watermarking based on energy comparison technique implementation using internet of things

Abstract

This paper introduces a new audio watermarking technique based on a perceptual kernel representation of audio signals (spikegram). Spikegram is a recent method to represent audio signals. It is combined with a dictionary of gammatones to construct a robust representation of sounds. In traditional phase embedding methods, the phase of coefficients of a given signal in a specific domain (such as Fourier domain) is modified. In the encoder of the proposed method (twodictionary approach), signs and phases of gammatones in the spikegram are chosen adaptively to maximize the strength of the decoder. Moreover, the watermark is embedded only into kernels with high amplitudes where all masked gammatones have been already removed. The efficiency of the proposed spikegram watermarking is shown via several experimental results. First, robustness of the proposed method is shown against 32 kbps MP3 with an embedding rate of 56.5 bps. Second, we showed that the proposed method is robust against unified speech and audio codec (24 kbps USAC, linear predictive and Fourier domain modes) with an average payload of 5-15 bps. Third, it is robust against simulated small real room attacks with a payload of roughly 1 bps. Lastly, it is shown that the proposed method is robust against a variety of signal processing transforms while preserving quality.