Auditory_Unveil

Uses audio analysis along with a Convolutional Neural Network model to detect emotions in speech.

Overview

This project focuses on using audio analysis techniques in combination with a Convolutional Neural Network (CNN) model to detect emotions in speech. It's designed to provide a framework for understanding and recognizing emotions in spoken language, which has practical applications in various fields, including human-computer interaction, sentiment analysis, and mental health monitoring.

Features

• Audio Preprocessing: Utilize audio processing libraries to extract relevant features from speech signals.
• Convolutional Neural Network: Implement a CNN model to learn emotional patterns from audio data.
• Emotion Classification: Identify emotions such as happiness, sadness, anger, and more.
• Visualization: Visualize emotions through graphs, spectrograms, or other graphical representations.

Installation

1. Clone the repository to your local machine:

   git clone https://github.com/sudocanttype/Auditory_Unveil.git
   cd Auditory_Unveil

2. Install the Python dependencies

   pip install -r requirements.txt

3. Run the Jupyter Notebook

   jupyter notebook ACM2023.ipynb