## 4 Experimental Results
### Experiments on Mono Audio
(**b**) CSNR of “Classical Music” audio. (**c**) The sum of CSNR histograms of seven test audio signals. Delay is also a significant factor which influences the performance of the proposed algorithm. If the delay is too large, the accumulation samples for calculating autocorrelation will decrease, which will cause an increase in the BER. The results in Table 4 and Figure 11 show how the delay had and effect on the ODG and BER. We can see that the delay around 45 samples gave good result where the delay was less than 100%. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Data Payload (bps)** & **ODG** & **BER (\%)** \\ \hline
24 & \(-\)0.82 & 0.47 \\
48 & \(-\)0.66 & 0.61 \\
72 & \(-\)0.66 & 0.83 \\
96 & \(-\)0.66 & 1.77 \\
144 & \(-\)0.62 & 4.55 \\
192 & \(-\)0.57 & 8.77 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: ODG and bit error rate (BER) values under various data payloads. Figure 10: ODG and BER values under various passband frequencies. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Passband Frequency (kHz)** & **ODG** & **BER (\%)** \\ \hline
0.5–3.5 & \(-\)1.17 & 2.96 \\
1.5–4.5 & \(-\)0.86 & 1.22 \\
2.5–5.5 & \(-\)0.65 & 1.77 \\
3.5–6.5 & \(-\)0.77 & 5.34 \\
4.5–7.5 & \(-\)0.76 & 15.06 \\
5.5–8.5 & \(-\)0.68 & 45.76 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: ODG and BER values under various passband frequencies. Figure 9: ODG and BER values under various data payloads. ODG was over \(-1\) and the BER was under 3%. Though the ODG got better when delays were over 100 samples, BER rose over 3%  
Figure 12 and Table 5 show how the attenuation length at the boundary of the window influenced the BER and ODG. It can be observed that the ODG steadily rose as the attenuation length increased and the BER decreased. An attenuation length of 10-25 is preferable, as the BER increased quickly over 25, and the ODG was relatively low at 5. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Delay** & **ODG** & **BER (\%)** \\ \hline
15 & \(-0.77\) & 2.65 \\
45 & \(-0.66\) & 1.77 \\
75 & \(-0.56\) & 2.1 \\
100 & \(-0.44\) & 3.29 \\
150 & \(-0.23\) & 7.23 \\
200 & \(-0.03\) & 21.12 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: ODG and BER values under various delays. Figure 11: ODG and BER values under various delays. Figure 12: ODG and BER values under various attenuation lengths of the window. In Table 6, we illustrate our comparison results. Our comparison was based on reported results of recently published papers [8; 9; 12; 13; 23; 24] and was given for the data payload, ODG, and BER under MP3 compression (32 kbps, 64 kbps, 96 kbps, 128 kbps). We also listed the BER under various HE-AAC v1 compression bitrates (16 kbps, 24 kbps, 32 kbps, 64 kbps) with various data payloads. As we can see from the table, the proposed algorithm is competitive compared with other methods at similar data payloads under MP3 compression, indicating that our algorithm is also able to be robust against MP3 compression. Comparing the BER at the same bit rate (32 kbps, 64 kbps) on MP3 and HE-AAC v1 compression of our algorithm, we found that the BER under HE-AAC v1 was nearly half of the MP3. From the BER results at various HE-AAC v1 compression bitrates, we can see that our algorithm was able to be robust against HE-AAC v1 compression where the bit rate was higher than 24 kbps with a low BER. Unfortunately, we could not have a comparison result under HE-AAC v1, as there is no paper which has evaluated its robustness under HE-AAC v1 compression.