Awarded most innovative project. Fourth year capstone project that can predict human emotion through vocal input using machine learning techniques (Keras & Tensorflow).
This project set out to determine the emotion of the user based on only vocal analysis. To do this a convolutional neural network was used to train a model that could predict emotions with ~%80 accuracy.
Here is the tech used to create this project.
Jacob Chambers - LinkedIn - jake_chambers12@hotmail.com
- Install virtualenv: https://uoa-eresearch.github.io/eresearch-cookbook/recipe/2014/11/26/python-virtual-env/
- Make sure you have python 3.7 installed on you computer. You can download it here at: Python
- Once you have your virtualenv installed, cd to the directory which your virtual env is stored. Next run this command:
virtualenv --python=/Library/Frameworks/Python.framework/Versions/3.7/bin/python3 ./emotional/ - Next, run your virtualenv.
- Once in your virtualenv, cd to the directory where eMotionaL was downloaded then cd into eMotional.
6. Run:
pip install -r requirements.txt. This will install all the required dependencies. - cd into the second eMotionaL folder in the project and then run:
python server.py. This will host eMotionaL at: http://localhost:5000/