SentimentZen utilizes emotion analysis to understand a user's current emotional state based on their input. Leveraging this data, the platform offers a suite of features to guide users towards a more positive emotional state.
- Input Options: Users can input text directly or use speech input for analysis.
- Emotion Analysis: Utilizes the RoBERTa model to analyze the input and detect emotions across 28 different labels.
- Content Recommendations: Recommends books, movies, music, and yoga/meditation practices tailored to the user's emotional needs.
- Interactive Visualization: Displays the emotional analysis results using a bar chart for easy visualization.
- Dr. Zen: An AI-powered therapist chatbot offering personalized support, practical advice, and empathetic listening.
React: Frontend framework for building the user interface.
RoBERTa Model: Pre-trained transformer model from Hugging Face for emotion analysis.
Chart.js: JavaScript library for creating interactive charts.
SpeechRecognition API: Enables speech input functionality.
Google Gemini API: Powering the Dr. Zen feature which is an AI Therapist chatbot.
Hugging Face Datasets: Provides the emotion dataset for training and analysis.
- Clone the repository
git clone https://github.com/saurabhsinghaa/SentimentZen.git
cd SentimentZen- Install dependencies
npm install- Start the Development Server
npm start- Start the Development Server
Open your web browser and navigate to http://localhost:3000 to access the SentimentZen application.
