A cross model translation system from Speech to Indian Sign Language along with an emotion recognition system. The model uses Uberi Speech Recognition API which takes real-time speech input, convert it to text and then the model generates sign language symbols for that. Used Natural Language Toolkit (NLTK) to add sentiment analysis support which uses 2-way polarity (positive & negative) classification system for the input. The model uses a dictionary-based machine translation-system and the user interface for the project has been designed using EasyGui.
The model consist of a sub-part - Text-Emotion-Recognition which consist of an LSVM model for sentiment analysis. And the trained model is then dumped in the form of a pickel which is later used in the final application so as to avoid training it for every single time.
- Clone this repository using terminal:
git clone https://github.com/theDeepanshuMourya/Signify - Extract the zip file and then open terminal in the Signify folder.
- Now run:
python main.py - Now the program will ask for a live voice input.
- Provide an input using microphone and see the results. Happy Translation 👍
- Fork it!
- Create your feature branch:
git checkout -b my-new-feature - Commit your changes:
git commit -am 'Add some feature' - Push to the branch:
git push origin my-new-feature - Submit a pull request 😄
Check the link in the description for a working model walkthrough.