title: Sise Challenge Emotional Report
emoji: 🎤
colorFrom: yellow
colorTo: green
sdk: docker
pinned: false
SISE Ultimate Challenge - Emotional Report
Welcome to Emotional Report! This AI-powered application lets users send or record an audio clip 📢, analyzing their emotional state based on vocal tone and speed. The AI predicts whether the emotion falls into one of three categories: Anger (Colère) 😡, Joy (Joie) 😃, or Neutral (Neutre) 😐.
Using Wav2Vec, a pre-trained AI model, the app not only detects emotions but also attempts to transcribe the speech into text. 🧠🎙️
🎬 Fun Fact
The name Emotional Report is inspired by the movie Minority Report, where AI predicts crimes before they happen! 🔮 This challenge is the Ultimate Challenge for Master SISE students. 🏆
👀 Overview
This project features a Streamlit-based dashboard 📊 that helps analyze security logs, data trends, and apply machine learning models.
✨ Features
✅ Home - Overview of the challenge 🏠 ✅ Analytics - Visualize & analyze security logs and data trends 📈 ✅ Machine Learning - Train & evaluate ML models 🤖
🚀 Installation Guide
🔧 Local Setup
Follow these steps to run the project locally:
- Clone the repository:
git clone https://github.com/jdalfons/sise-ultimate-challenge.git cd sise-ultimate-challenge - Create and activate a virtual environment:
python3 -m venv venv source venv/bin/activate # On Windows, use `venv\Scripts\activate` - Install dependencies:
pip install -r requirements.txt - Run the Streamlit application:
streamlit run app.py
🐳 Docker Setup
- Build the Docker image:
docker build -t sise-ultimate-challenge . - Run the container:
docker run -p 7860:7860 sise-ultimate-challenge
⚙️ Technical Details
- 🐍 Python 3.12
- 🎨 Streamlit
- 🎙️ Wav2Vec2
🤝 Contributors
🔥 Join us in making AI-powered emotion detection awesome!