## 4 Experimental Results
### Experiments on 5.1 Channel and Stereo Audio
\begin{table}
\begin{tabular}{c c c} \hline \hline
**No.** & **Audio Name** & **Description** \\ \hline
1 & [PERSON] organ & Church organ; lots of stops out \\
2 & Brass & Orchestral; lots of brass instruments \\
3 & Harpsichord & Solo harpsichord; isolated notes \\
4 & Mouth harp & Mouth organ, bass guitar, percussion \\
5 & Sax Piano & Saxophone and piano \\
6 & Trumpet & Orchestral piece \\
7 & Applause & Applause with distinct clapping sounds \\
8 & Chants & Small choir; large church; Gregorian chant \\
9 & Classical & Orchestral piece; open sound \\
10 & Radio drama & Clarinet, orchestra, male speaker, tenor, ambience \\
11 & Sedambonjou & Atmospheric performance of Latin-American music \\
12 & Moonriver & Mouth organ and string orchestra \\ \hline \hline \end{tabular}
\end{table} 
Table 7: 5.1 channel host audio used in the experiment. Figure 13: Time domain waveforms of the “[PERSON] organ” 5.1 channel audio. Furthermore, we present the BER of the multichannel audio under various bit rate HE-AAC compressions in Table 10. It can be seen that our watermarking algorithm was able to be robust against HE-AAC v1 and HE-AAC v2 compression when the bit rate was higher than 128 and 32 kbps, respectively, for 5.1 channel and stereo audio, as the BER was under 3% at a data payload of 96 bps, and the ODG was larger than \(-1\). However, our algorithm showed a bad robustness for extremely low bit rate compression, like 5.1 channel audio with HE-AAC v1 64 kbps and stereo audio with HE-AAC v2 16 kbps, where the BER was over 20%. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**No.** & **FL** & **FR** & **C** & **LFE** & **SL** & **SR** & **Avg BER** & **ODG** \\ \hline
1 & 2.93 & 6.21 & 0.18 & — & 3.87 & 5.21 & 3.68 & \(-\)0.70 \\
2 & 3.95 & 2.44 & 0.29 & — & 5.03 & 1.94 & 2.73 & \(-\)0.84 \\
3 & 0.88 & 1.24 & 0.12 & — & 1.18 & 0.65 & 0.81 & \(-\)1.06 \\
4 & 1.87 & 1.74 & 0.37 & — & 1.55 & 1.99 & 1.51 & \(-\)0.73 \\
5 & 3.83 & 3.32 & 0.22 & — & 0.30 & 0.30 & 1.59 & \(-\)0.54 \\
6 & 3.81 & 1.57 & 0.00 & — & 3.47 & 2.35 & 2.24 & \(-\)0.86 \\
7 & 0.06 & 0.24 & 0.77 & — & 1.42 & 4.56 & 1.41 & \(-\)0.48 \\
8 & 0.59 & 1.00 & 2.17 & — & 0.06 & 1.00 & 0.96 & \(-\)0.86 \\
9 & 4.90 & 3.74 & 0.27 & — & 2.76 & 3.48 & 3.03 & \(-\)1.14 \\
10 & 7.84 & 8.67 & 0.46 & — & 8.39 & 9.03 & 6.88 & \(-\)0.93 \\
11 & 2.78 & 2.83 & 0.64 & — & 2.95 & 2.78 & 2.39 & \(-\)1.04 \\
12 & 3.47 & 4.02 & 0.64 & — & 3.29 & 4.48 & 3.18 & \(-\)0.95 \\
**Avg** & **—** & **—** & **—** & **—** & **—** & **2.53** & **-0.84** \\ \hline \hline \end{tabular}
\end{table} 
Table 8: BER (%) and ODG of each channel of 5.1 channel audio under HE-AAC v1 128 kbps compression. Figure 14: Time domain waveforms of the “Bach organ” stereo audio. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**No.** & **Left Channel** & **Right Channel** & **Avg BER** & **ODG** \\ \hline
1 & 0.70 & 1.70 & 1.20 & \(-\)0.42 \\
2 & 0.57 & 0.93 & 0.75 & \(-\)0.78 \\
3 & 0.35 & 0.88 & 0.62 & \(-\)0.98 \\
4 & 0.56 & 0.12 & 0.34 & \(-\)0.62 \\
5 & 1.62 & 0.81 & 1.22 & \(-\)0.73 \\
6 & 1.01 & 0.78 & 0.90 & \(-\)0.83 \\
7 & 0.06 & 0.06 & 0.06 & \(-\)0.45 \\
8 & 0.18 & 0.64 & 0.33 & \(-\)0.83 \\
9 & 1.78 & 0.45 & 1.12 & \(-\)1.07 \\
10 & 3.19 & 3.01 & 3.10 & \(-\)0.87 \\
11 & 4.80 & 4.40 & 4.60 & \(-\)0.87 \\
12 & 1.10 & 1.19 & 1.15 & \(-\)0.89 \\
**Avg** & **—** & **—** & **—** & **1.28** & **-0.78** \\ \hline \hline \end{tabular}
\end{table} 
Table 9: BER (%) and ODG of each channel of stereo audio under HE-AAC v2 48 kbps compression.