Robust Audio Watermarking Based on Iterative Filtering

The digital media shared over the Internet is the backbone of the current generation of communication. Multimedia is becoming increasingly popular with no governing body for intellectual property rights, hence the need for protecting it efficiently while preserving the feature set of given data. Several watermarking methods have been proposed for the copyright protection of audio and speech signals yet the Recording Industry Association of America reported illegal downloading costs around $12.5 billion in the year 2021. Furthermore, the challenge to find the right balance between the three contrasting characteristics of watermarking; robustness, imperceptibility, and payload persists. This paper puts forward a new, hybrid, and purely data-driven way of watermarking the audio and speech signals using iterative filtering and singular value decomposition. The input audio is processed using iterative filtering to generate a band of intrinsic mode functions (IMFs) and a residue component. Depending upon the application, singular value decomposition is applied on residue or an IMF for insertion of bits of the watermark to minimize the effect of watermarking on the audio signal. The method focuses on the robustness of the audio signals against various signal processing attacks while providing a significant boost in imperceptibility and payload as well. Thus, providing a strikingly excellent balance between the characteristics of watermarking. With an average SNR of 38.06 db and normalized correlation close to unity, the proposed method validates its superiority compared to the state of the art.