VoiceAI-Conversationalist

VoiceAI-Conversationalist is a voice-activated AI-based application that enables users to engage in real-time, two-way conversations with an AI system. Built to assist users with career guidance, tech advice, and job search tips, the application listens to user queries and provides relevant AI-generated responses. This project includes frontend and backend components to manage voice processing, conversation storage, and user authentication.

Table of Contents

• Features
• Architecture
• Technologies Used
• Setup and Installation
• Environment Variables
• Usage
• Contributing

Features

• Real-Time Conversation: Users can engage in voice-based conversations with the AI.
• Voice Recognition & Synthesis: Uses Web Speech API to recognize user speech and synthesize AI responses.
• Dynamic AI Responses: Provides personalized responses based on the user’s input (e.g., "Who are you?", "career advice").
• Conversation History: Securely saves conversations, allowing users to view past exchanges.
• Authentication: Users can register, log in, and access their personal conversation history.

Architecture

• Frontend: Built with React (TSX) and Vite, handling voice input and response display. Includes user registration, login, and settings for conversation control (e.g., voice speed, pitch).
• Backend: Node.js with Express, handling AI response generation, user authentication, and conversation storage in MongoDB. AI responses are customized based on keywords.
• Database: MongoDB is used to store user profiles, conversation history, and AI responses.
• Speech Processing: Web Speech API for recognition and Speech Synthesis API for AI voice output.

Technologies Used

• Frontend: React, Vite, TypeScript, Tailwind CSS, React Router DOM
• Backend: Node.js, Express.js, Mongoose, Passport.js
• Database: MongoDB

Setup and Installation

Prerequisites

• Node.js
• MongoDB

Installation

1. Clone the Repository:

   git clone https://github.com/yourusername/VoiceAI-Conversationalist.git
   cd VoiceAI-Conversationalist

2. Install Dependencies:

   • Backend:

     cd server
     npm install

   • Frontend:

     cd ../client
     npm install

3. Environment Variables: In the server folder, create a .env file and add the following variables:

   MONGO_URI=your_mongodb_connection_string
   JWT_SECRET=your_jwt_secret
   

4. Run the Application:

   • Start the backend:

     cd server
     npm run dev

   • Start the frontend:

     cd ../client
     npm run dev

5. Access the Application: Visit http://localhost:3000 in your browser.

Environment Variables

Ensure the following environment variables are set up in your .env file:

Variable	Description
MONGO_URI	Connection string for MongoDB
JWT_SECRET	Secret key for JSON Web Token (JWT)

Usage

1. Registration/Login: Users register and log in to store and view their conversation history.
2. Starting a Conversation: Click "Start Conversation" to begin speaking with the AI. The AI listens, responds, and displays both the user’s query and AI’s response.
3. Conversation History: Users can view past conversations stored securely under their account.
4. Voice Settings: Users can adjust voice speed, pitch, and tone for a personalized experience.

Example Conversation

• User: “Hello!”
  • AI: “Hello! How can I assist you today with your career or tech questions?”
• User: “Can you give me some job search tips?”
  • AI: “Sure! Here are some useful job search tips...”

Contributing

1. Fork the repository.
2. Create a feature branch (git checkout -b feature-name).
3. Commit your changes (git commit -m "Add new feature").
4. Push to the branch (git push origin feature-name).
5. Open a pull request.

Coding Guidelines

• Backend: Separate logic by grouping into controllers, models, and utilities for maintainability.
• Frontend: Ensure components are modular and reusable.

Certainly! Here’s a tip section that you can add to the README for guiding users on crafting questions for better AI responses:

Tip: Enhancing AI Responses

For more relevant and engaging responses from the AI, check the keywords and phrases that trigger specific answers. You can find these in the aiResponseGenerator.js file located in the server folder. Incorporating these keywords (e.g., "career," "tech field," "job search tips") in your message can help guide the AI to respond with information that best matches your query.