Natural Language Translation Project

This project has the following goals:

• Create a Machine Translation System application, based on the Recurrent Neural Network with Keras deep learning model.
• Implement a haiku generator using character-level multi-layer Recurrent Neural Network model.
• Deploy the application.

Results:

• Language Model was trained on 100 000 pairs for each language (English - Spanish and English - French) and is able to translate short phrases like 'where is the bathroom', 'give me a fork', 'I like to swim' etc.
• Haiku Model generates haiku, that sound close to the haiku rules
• Application was deployed

Steps of project:

1. Data acquisition, cleaning and preparation of dataset.
2. Building model with Keras.
3. Model training (Test-Train).
4. Developing Flask app.
5. Developing Front-end.
6. Deploying.

Local use:

• Install all necessary libraries.
• Proceed to local_app --> app folder.
• Run app.py
• Open localhost http://127.0.0.1:5000/

Team Members:

• Christina Park
• Malvika Mathur
• Ed Ali
• Sonya Smirnova
• Abubeker Ali

Tools Used:

• Python
• Tensor Flow
• Keras
• Pandas
• BeautifulSoup
• MongoDB
• Selenium
• Flask
• JavaScript
• HTML

Output of the project