## 3 Results
### Identifying the Chain of Commands Used
#### 3.2.2 Prototype Creation and Validation  
Using the results of the Wizard of Oz experiment and the survey, a system prototype was developed to help design technology for a VUI and to collect results in a near-to-reality scenario. This prototype consisted of three parts. First, a server was needed to receive and respond to requests for processing instructions and store the interactions in a database. This was developed using Spring Boot and used an h2 database. Second, a package was devised to process the instructions in natural language and create the appropriate answer in each case. In this prototype, the package was built with JavaCC, a parser generator, using the specifications obtained from the first and second experiments. In the third and final part, the client would oversee the map display provided by WebGL Earth (Figure 8), an open-source virtual planet application, and send requests to the server with the text recognized by the Annyang library, which exposes the functionalities of the WebSpeech API interface. Web Speech API is a JavaScript interface supported by most browsers for speech recognition and synthesis.  
The prototype could respond to instructions and operate like any map browser using voice alone. It could provide feedback in the form of the recognized text, which was essential in case the system confused instructions for similar words (e.g., nine and move). It could also search for toponyms through the MapQuest API, but correct toponym recognition  
Figure 8: Prototype interface.  
could be challenging in other languages or with difficult or variable pronunciation. A video demo showing the prototype in use is provided as additional material (File S3).  
The prototype was validated to determine if it could fulfil the requirements of the previous experiments (survey, and Wizard of Oz + interviews) through another scenario experiment based on the Wizard of Oz tasks. As those tasks covered the functionalities comprehensively, the prototype test results could be compared with the ideal system simulated by a human successfully to validate the prototype according to the original specifications. As in the previous experiment, observer intervention was minimized to replicate a natural interaction with the system. The real prototype in operation allowed for interactions to be automatically recorded, facilitating various measures we carried out, such as calculating the success rate of the instructions. The COVID-19 pandemic constrained the experiment in part, forcing testing to be performed online, with a sample of eight. This approach limited our ability to observe during the experiment, but we countered this by using two communication tools simultaneously, one for the user's webcam and another for the user's screen.  
The validation was successful, confirming the fixed requirements of the previous experiments were met. When implementing only the most popular verbs for actions, we observed that, in the case of a failure due to an unrecognized term, users quickly switched to a more frequently used term. Only one user of those interviewed expressed that he would not use it in his daily life, and the average rating was 3.8 out of 5.  
The source code for the prototype is provided as additional material, free to use and modify (File S2).