  Graph-based Transform (GT) has been recently leveraged successfully in the
signal processing domain, specifically for compression purposes. In this paper,
we employ the GBT, as well as the Singular Value Decomposition (SVD) with the
goal to improve the robustness of audio watermarking against different attacks
on the audio signals, such as noise and compression. Experimental results on
the NOIZEUS speech database and MIR-1k music database clearly certify that the
proposed GBT-SVD-based method is robust against the attacks. Moreover, the
results exhibit a good quality after the embedding based on PSNR, PESQ, and
STOI measures. Also, the payload for the proposed method is 800 and 1600 for
speech and music signals, respectively which are higher than some robust
watermarking methods such as DWT-SVD and DWT-DCT.
