/natural-language-translation

Natural language translation with Keras

Primary LanguageJupyter Notebook

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

project.png