## 6 Conclusions  
In this paper, a novel and blind audio watermarking algorithm with strong robustness is proposed according to the multi-resolution characteristic of DWT and the energy compression capability of DCT. The cover audio signal is first segmented into audio fragments, and then each audio fragment is performed by DWT and DCT in order to obtain two sets of TDC which are modified to embed the binary watermark. This proposed algorithm can realize blind extraction of digital watermark without the participation of carrier audio signal when extracting watermark, which is convenient for the practical application. The embedding depth is the key factor to determine the performance of the algorithm. In the case that the algorithm has good imperceptibility, the embedding depth should be increased to improve the robustness. The experimental results show that the average SNR of the carrier audio signals reaches 23.49 dB in the case of the payload capacity of 172.27 bps, which indicates that this proposed algorithm has large capacity and good imperceptibility. In addition, this proposed  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Attack** & **Proposed** & **Paper [4]** & **Paper [16]** & **Paper [25]** & **Paper [12]** & **Paper [19]** \\ \hline A & 0.01 & 0.39 & 21.97 & 28.25 & 0.12 & 6.93 \\ B & 0.01 & 2.87 & 0.50 & 0.30 & 0.12 & N/A \\ C & 0.01 & 17.92 & 0.47 & 0.35 & N/A & N/A \\ D & 2.27 & N/A & N/A & N/A & 1.29 & N/A \\ E & 0.22 & N/A & N/A & N/A & 0.31 & N/A \\ F & 0.07 & 0.78 & N/A & N/A & N/A & 0.00 \\ G & 0.08 & 1.95 & 2.45 & 6.85 & 0.12 & 0.00 \\ H & 0.01 & N/A & 1.12 & 4.97 & 1.61 & 0.00 \\ I & 0.01 & 0.00 & 1.00 & 6.45 & 0.12 & 0.00 \\ J & 0.14 & 0.78 & N/A & N/A & 0.12 & 0.00 \\ K & 0.01 & N/A & N/A & N/A & 0.84 & N/A \\ \hline \hline \end{tabular} Note that N/A means no report is found in the selected algorithm.  
\end{table}
Table 2: Average BER values (%) of the extracted watermarks under different attacks.  
algorithm has excellent robustness against white noise, low-pass filtering, re-sampling, re-quantization, echo addition, amplitude scaling and MP3 compression compared with other audio watermarking algorithms. Without synchronization signal, the watermark extraction begins with the first audio fragment, so this algorithm cannot combat the desynchronization attack, although it can effectively resist the conventional signal processing attacks generated during the use of audio media. In the next study, we will focus on the issue of how to add synchronization signals in the carrier audio, as well as the problem of combating other types of attacks, such as desynchronization attack, collusion attack type II and strong noise corruption.  
[PERSON] conceived the algorithm and designed the experiments; [PERSON] performed the experiments; [PERSON] and [PERSON] analyzed the results and adjusted the experimental scheme; [PERSON] drafted the manuscript; [PERSON] and [PERSON] revised the manuscript. All authors read and approved the final manuscript.  
This research work was supported by the National Natural Science Foundation of China for Youth, China (Grant No. 61602263), Research and Innovation Project for Graduate Students of Jiangsu Province, China (Grant No. KYLX_0815), the University Natural Science Foundation of Jiangsu Province, China (Grant No. 16 KJB510015).  
The authors declare no conflict of interest.