## 5 Discussion  
The prototype VES has been conceived and developed as a versatile tool which allows the implement and testing of non-visual human-machine interfaces for BVI navigation in both virtual and real scenarios. The tests described in the previous section have validated its potential in this regard. Also, the tests conducted provide a few cues about GbVAS' effect on orientation and mobility tasks. Nevertheless, a more detailed analysis of a more extensive population of both normal-sighted and BVI individuals is required.  
Coherently with the experiments' design, most of the test subjects identified regions in which acoustic cues were generated, as well as GbVAS' virtual areas which moved according to head movements. After only six minutes training, they were able to use the prototype to perceive key features of the environment. The usage of natural data encoding is considered to play a key role in this respect.  
Nevertheless, the spatial boundaries of nearby elements and GbVAS virtual areas tended to be distorted when there is no prior knowledge on the prototype's output nor the scenario.  
In Test 1, Group A tended to overestimate the size of the columns. This is probably due to an underestimation of PVAS' field of view and lack of training, as an object's size could be inferred from the acoustic image. However, these results did not occur in a known environment (Test 3). On the other hand, Group B tended to correctly estimate the columns' size, probably because of a redundancy in PVAS and AVAS output.  
However, in Test 2 Group B performed poorly compared with Group A. Again, they tended to interpret AVAS output as heading cues, and were therefore lured inside the walls. Outside of the experimental setup, experimented users of GbVAS used AVAS to improve mobility performance. In future experiments, it will be tested whether the subjects' navigation behavior changes if they are provided with a few notions of AVAS operation.  
Another key result of these experiments is that PVAS and AVAS could be used at the same time by Group B. Therefore, the required bandwidth and cognitive load was low enough to avoid overloading the user. For future research, it would also be important to test whether VES can be used by the targeted public without masking key auditory feedback from the actual environment.  
These results also account for the importance of bias, as the low resolution of VES does not allow the identification of features which were drawn in the sketches, e.g., the shapes of the columns in Test 1. Even simple messages can condition perception, and the development of a mental representation of the environment. Therefore, this highlights the potential of verbal interfaces in this regard.  
Finally, the feedback provided by the subjects can be summarized in two main points. Firstly, a detailed explanation on GbVAS operation is needed, although some of the users were able to decode the data output by themselves through a trial-and-error process. Secondly, AVAS data-encoding proved to be difficult to assimilate, although its range of effect effectively complemented PVAS once the user became familiar with it. Therefore, this human-machine interface algorithm might be further enhanced with novel spatial data encoding while maintaining AVAS's virtual area.