we have developed Emotion Detection Using DL algorithms.
This project contains two deep learning models for emotion detection: one for analyzing text and another for analyzing speech.
Text Emotion Detection Algorithm :-
The text emotion detection algorithm is based on an Artificial Neural Network (ANN) and achieves an accuracy of 85%. The algorithm is built using Python and Flask, making it easy to integrate into web applications.
Speech Emotion Detection Algorithm :-
The speech emotion detection algorithm uses a combination of Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) networks. The CNN analyzes the acoustic features of the speech, while the LSTM analyzes the temporal aspects of the speech signal. The algorithm achieves an accuracy of 52% with LSTM and 72% with CNN.
GUI :-
The graphical user interface (GUI) is built using Tkinter for Speech Emotion Detection and in Flask for Text Emotion Detection. It provides a user-friendly interface for interacting with the models and getting real-time emotion detection results.
Installation and Usage :-
To use this project, you will need to have Python 3 installed. Clone the repository and install the necessary packages using the following command:
Here is a quick glance to Text Emotion Detection App :
MADE BY :-
Prarthana Galani - 20BCE072
Nishi Patel - 20BCE179
Deep Pajpani - 20BCE184
Jinesh Patel - 20BCE206