Multi-subspace Echo Hiding based on Time-Frequency Similarities of Audio Signals

Audio watermarking plays an important role in copyright protection. Echo hiding, one of the most effective techniques for audio watermarking, has been studied for decades. However, the conventional echo hiding has been criticized for its weak security, as watermarks can be easily extracted by means of cepstrum analysis even without any prior knowledge. This article explores the time-frequency (T-F) characteristics of the repetition structures in an audio signal to improve the security of conventional echo hiding. In our approach, the original audio signal is first converted into a high-dimensional T-F representation, and then by clustering the time frames that have similar T-F characteristics into the same subspace, the original audio is decomposed into a union of subspaces with each corresponding to one time-domain subsignal. Paired and opposite echo kernels are applied to energy-balanced subsignals for watermark embedding, which significantly improves the security. In the watermark extraction process, the subspaces are recovered on the basis of the T-F similarities and cepstrum analysis is utilized to extract watermarks. The proposed embedding and extraction schemes thus offer a new approach for echo hiding. The results of experiments demonstrate the effectiveness of our approach with respect to inaudibility, security, and robustness.