# AMBIQUAL: Towards a Quality Metric for Headphone Rendered Compressed Ambisonic Spatial Audio
## 6 Discussion and Ongoing Work  
AMBIQUAL has been shown to be capable of predicting spatial audio QoE in terms of both localization accuracy and listening quality. Both single point and multiple point sound source experiments show good correlation between objective model predictions and subjective MUSHRA scores (see Table 6). Future work will be focused on more complex sound scenes. The trends exhibited in the aggregated subjective results (as shown in Figures 11a and 12a,b) are replicated by the aggregated objective results (as shown in Figures 11b and 12c,d). This is true for both single and multiple point audio sources for all conditions tested. It can be seen that the model can predict the difference in quality independently of the test sample content. This is apparent by inspecting the clustering of data points by condition (i.e., bitrate and compression scheme). It is evident for both single point audio sources as shown in Figure 12e and \begin{table}
\begin{tabular}{l l l l l l l} \hline \hline \multicolumn{3}{c}{**Listening Quality**} & \multicolumn{3}{c}{**Localization Accuracy**} \\ \hline  & **Pearson** & **Spearman** & **RMSE** & **Pearson** & **Spearman** & **RMSE** \\ \hline
1 & 0.899 & 0.816 & 55.14 & 0.922 & 0.919 & 59.27 \\ \hline
2 & - & - & - & 0.864 & 0.883 & 63.13 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Correlation between subjective MUSHRA and objective AMBIQUAL results from experiments 1 and 2. Figure 16: Localization accuracy as a function of azimuth and elevation. A fixed reference audio source is located at an offset point of azimuth = 30\({}^{\circ}\), elevation = 30\({}^{\circ}\). The asymmetry in results is caused by the source being closer to one ear than the other. multiple point audio sources as shown in Figure 12f. This observation is further reinforced by the lack of clustering by sample type presented in the two scatter plots in Figure 12g.h. In this paper, we have presented the AMBIQUAL algorithm which is still at an early developmental stage. The authors are aware that the experiments presented are limited in scope in terms of source number (one or two) and codec used (Opus 1.2) but work is ongoing to test more realistic scenarios with a wider range of compression schemes which share spatial information across the Ambisonics channels. In [3], a discussion about how listeners judge listening quality and localization accuracy from a QoE perspective is presented. More specifically, can localization accuracy and listening quality be judged independently, or do listeners penalize listening scores if there are localization accuracy issues? This remains an open question. In current research, spatial audio is characterized using a variety of spatial and non-spatial attributes. The weighting factors shown in Figure 10 have been empirically derived. It would be interesting to explore how the directivity associated with the corresponding spherical harmonics contribute to the perceived localization accuracy results and more general models of localization selectivity. Spatial attributes include scene depth and localization accuracy while non-spatial attributes include brilliance and distortion. As such, investigators need to decide whether or not to include non-spatial attributes in quality assessment [40]. State-of-the-art methods from multidimensional quality assessment [23] are recommended until relevant standards are agreed upon. AMBIQUAL represents a simpler alternative to existing methods of assessing Ambisonics spatial audio. Such methods carry out assessment on binaural renders of several head positions which is not as appealing as AMBIQUAL, which can assess spatial audio quality directly from the Ambisonics format. These early results and the computational simplicity of the method support the proposed further research which will generalize and optimize the approach for higher-order Ambisonics formats. [PERSON], [PERSON], [PERSON], [PERSON] and [PERSON] contributed equally to conceptualization.