¿ Como Se Dice ?

A platform to help spanish speaking farm workers learn English. It parses Berkley’s Agricultural Personnel Management english learning resources to create a centralized and interactive location for learning English.

• Live demo video can be seen here

• Deployed here. Heroku takes around 20 seconds to startup the server.

Features

• User are able to learn and practice over 300 vocabulary words and phrases by using flashcard with audio playback
• Users are able to test their skills by taking quizzes for each vocabulary card category
• Users are able to track their progress by reviewing their dashboard which contains stats for questions they've gotten incorrectly, alongside their weekly activity.
• Users are able to translate text from English to Spanish and Spanish to English by typing their text or by speaking it.
• Users are able to create and delete custom vocabulary cards along with their audio.

Getting Started

If you'd like to test this version of the app on your local system you can do so by following the steps below:

1. Navigate to your desired directory and git clone the repo url
2. Open the backend folder and run bundle install
3. Start the service with rails s
4. Navigate to the frontend folder and type npm start
5. The app will open in a new Chrome window and you should now be able to test out it's features by signing up for a new user.

Built With

• React JS - I used React to build the user interface and to manage the flow of the app.
• Ruby on Rails - I used Ruby on Rails to handle the back-end logic.
• Material-ui - Material-ui and custom css were used for styling the app.
• Charts JS - Charts JS was used to display user stats on the dashboard.
• PostgreSQL - PostgresSQL was used for storing all app data.
• ActiveModelSerializers - ActiveModelSerializers were used for organizing backend API responses.
• Google Translation API - The Google Translate API was used to handle API English and Spanish translation.
• React-speech-recognition - React speech recognition was used to allow users to dictate translation text and translation commands.
• Amazon S3 - An Amazon S3 object was used to store audio files.
• Cloudinary - Cloudinary was used to store file uploads.

Authors

• Cristian - Cristian

License

This project is licensed under the MIT License - see the LICENSE.md file for details