While traveling, tourist and visitors are often hit with the inability to communicate effectively in the local language, whether that be French, German or Japanese. This can cause issues from ordering food to getting directions from the locals. This could be easily resolved if everyone had access to a quick, reliable service that helped you with the local language, no internet connection required.

What it does

Local Language Assistance (LLA for short) allows for people seeking help with the local language to be able to ask simple questions such as how to order a coffee at Tim Horton's and get fast responses from people fluent in the language. This means of language translation is better than automated services such as Google Translate as it comes straight from someone who is fluent in speaking the language and thus will be less prone to errors.

How we built it

LLA is built in Java and the Spark framework, using Twilio as the service that handlers the text messages. The app uses a database in order to keep track of the messages and forward the questions and answers to the appropriate people. The app and its dependencies are built and compiled using Maven and Gradle. All of this runs on a DigitalOcean virtual server.

Challenges we ran into

As we never used Twilio before, getting to know its intricacies and understanding its markup language were challenges we ran into. Additionally, as we used a trial Twilio account for this demonstration, we were limited in the functionality we could get from the Twilio service.

Accomplishments that we're proud of

Getting the app to compile! Seriously, (mostly because this was our first time making such an app) during the coding phase more often than not our work would not even successfully build, and we would have to debug our changes and work forward. I think finally getting the app to a functioning state is an accomplishment we're proud of.

What we learned

We learned a lot from this project, from using the Spark Java framework to sending and receiving text messages using the Twilio service. Furthermore, because of Twilio's extensive documentation, examples, and possible uses, there was quite a bit to learn in order to use it effectively.

What's next for Local Language Assistance

Get the app to a fully functioning state, allowing people to sign up as language helpers and for multiple people to communicate on the network simultaneously.

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