Sentiment Analysis with Voice Input

This project is a Sentiment Analysis Web Application with Voice-to-Text functionality. Users can input text manually or via voice, which is then analyzed for sentiment (positive, neutral, or negative) using a pre-trained BERT model from Hugging Face.

Features

• Voice Input: Click the microphone icon to speak, and your words will be transcribed to text.
• Sentiment Analysis: The backend uses a BERT-based model (bertweet-base-sentiment-analysis) from Hugging Face to analyze text sentiment.
• User-Friendly Interface: A clean, modern design with gradient backgrounds and card-based layouts for a smooth user experience.

Technologies Used

Frontend

• React: Component-based, dynamic rendering.
• Web Speech API: Captures and converts spoken input to text.

Backend

• Flask: Manages requests and responses.
• Transformers Library (Hugging Face): Utilizes bertweet-base-sentiment-analysis for text sentiment analysis.
• CORS: Handles cross-origin requests.

How to Run the Project

Prerequisites

Ensure you have the following installed:

• Node.js and npm (for frontend)
• Python and pip (for backend)
• Git (for repository management)

Setup Instructions

1. Clone the repository:

   git clone https://github.com/your-username/your-repo-name.git
   cd your-repo-name

2. Backend Setup:

   • Navigate to the backend folder:

     cd backend

   • Install Python dependencies:

     pip install -r requirements.txt

   • Start the Flask server:

     python app.py

3. Frontend Setup:

   • Open a new terminal and navigate to the frontend folder:

     cd frontend

   • Install Node.js dependencies:

     npm install

   • Start the React development server:

     npm start

4. Run the Application:

   • Open your browser and go to http://localhost:5173 to access the app.