## 2 Related Works
[PERSON] [25] proposed an adaptive method by modifying the average values of the wavelet-based entropy to embed the watermarks, but the robustness to re-sampling and low-pass-filtering attacks was quite low. An audio watermarking algorithm was proposed based on DWT in paper [26]. The algorithm changed the energy values of the former and the latter part of each audio fragment to hide confidential information. It had good robustness against several common attacks, but the author did not verify the robust performance when resisting MP3 compression which was the most common format for audio media. [PERSON] [27] presented a self-synchronized audio watermarking algorithm based on DWT byembedding the watermarks into the low frequency-band. The algorithm had large payload capacity, but its robustness was poor against MP3 compression and noise corruption. [PERSON] [28] proposed a self-synchronized audio watermarking method in which the synchronization code and the watermarks are embedded with the low-frequency sub-band in the DWT domain, but this algorithm has a high bit error rate (BER) against MP3 compression. [PERSON] [29] utilized a twofold strategy to embed the image watermark into audio signal based on SVD. The algorithm blended the watermark with the diagonal matrix holding singular values and then performed the second SVD on the modified matrix after applying the first SVD to a 2-D matrix. The matrices which contained left- and right-singular vectors must be conserved in order to extract the watermark. All the above algorithms were designed in a single transform domain. In recent years, there have been many audio watermarking algorithms in multiple transform domains. An audio watermarking algorithm against desynchronization attacks was proposed based on support vector regression in paper [31]. The algorithm used the support vector machines (SVM) theory to locate the optimal embedding positions, and embedded the watermarks into the statistical average value of low-frequency components in DWT and DCT domains. [PERSON] [32] proposed an audio watermarking algorithm according to the multi-resolution characteristic of DWT and the energy compression capability of DCT, but its robustness was poor against low-pass filtering and amplitude scaling. [PERSON] [33] utilized DWT and SVD to propose an adaptive audio watermarking by applying a quantization index modulation (QIM) process on the SVD values in the DWT domain. [PERSON] [34] presented a SVD-DWT blind watermarking algorithm to embed watermark into the audio signals in which the quantization steps were determined by the statistical properties of the involved DWT coefficients. [PERSON] [35] attempted to embed the watermark into the high frequency-band of the SVD-DCT block. They claimed the performance generally better than the previous SVD-based methods. [PERSON] [12] integrated discrete wavelet packet transformation (DWPT), SVD and QIM to achieve an approach for blind audio watermarking. The SVD was employed to analyze the matrix formed by the DWPT coefficients and embedded the watermarks by controlling singular values subject to perceptual criteria. [PERSON] [36] proposed a robust and blind audio watermarking algorithm based on SVD and QIM. Apart from the above algorithms, there are other audio watermarking algorithms in papers [4; 7]. [PERSON] [4] integrated exponent moments (EMs) and QIM to achieve an audio watermarking algorithm which used EMs to improve the robustness and QIM to realize the blind extraction of watermark, but this algorithm was not robust enough to resist amplitude scaling. [PERSON] [7] presented a reversible audio hiding scheme by using non-causal prediction. The scheme used the minimum error power method to calculate the optimum order and the prediction correlation of the audio data which could be used to embed the watermarks. It can be seen from the above introduction of the related works that the performance of the algorithms is not only related to the transform domain of signal processing, but also related to the embedding rules.