For this week, I was working on research for the speech and navigation aspects of our system. Specifically, I was identifying the different software components that would be required in translating the user’s speech, containing their desired destination, into inputs that can be used by the Google Maps API platform for retrieving the intended route. This is the tentative workflow for this process:
- Microphone receives location from user’s speech
- Google Speech to Text AI is used to extract destination from user’s speech
- Google Maps Geocoding API to translate location to Longitude and Latitude (Numerical Representation)
- Use the location information from JSON response with user’s GPS location to get route from Google Maps Direction API
- Each leg of journey is stored in a database so, each “leg” in the journey maps to an instruction at that point e.g. turn left on xxx road, turn right at yyy intersection
- The system will use the real-time GPS location to locate the closest leg of the journey and use that leg’s instruction for audio output to the user. The algorithm for figuring out closest leg to the current location is the R-tree algorithm.
For next week, I will be working on programming working demos that utilize the Google Speech APIs and Google Maps APIs. Additionally, I will be working on how to use the R-tree algorithm for the navigation system.For next week, I will be working on programming working demos that utilize the Google Speech APIs and Google Maps APIs. Additionally, I will be working on how to use the R-tree algorithm for the navigation system.