aiPitchEvaluator

Evaluate and Analyse Your Startup Pitch Voice with our AI powerd Application

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🎤 Audio Pitch Evaluator

A modern web application that analyzes and evaluates audio pitch presentations using AI-powered speech analysis and real-time audio processing.

✨ Features

  • 🎙️ Audio Recording - Browser-based recording with MediaRecorder API
  • 📊 Real-time Analysis - Comprehensive audio metrics including pace, volume, clarity, and confidence
  • 🤖 AI-Powered Evaluation - Uses Google Gemini AI for content analysis and feedback
  • 🎯 Detailed Scoring - Evaluates delivery, engagement, storytelling, and persuasiveness
  • 💾 Local Storage - Client-side storage using IndexedDB (no server uploads needed)
  • 🔄 Play/Pause Controls - Interactive audio playback with toggle functionality
  • 📈 Visual Dashboard - Clean interface showing all recordings and evaluation results
  • 💡 Detailed Feedback - Expandable cards with specific improvement suggestions

🛠️ Tech Stack

Frontend

  • React 18 with TypeScript
  • Vite - Fast build tool and dev server
  • Tailwind CSS - Utility-first styling
  • React Router - Client-side routing
  • Lucide React - Modern icon library
  • IndexedDB - Browser storage for audio files

Backend

  • Node.js with Express.js
  • Real Audio Processing - wavefile, node-wav, FFmpeg
  • Free Speech-to-Text - Hugging Face Whisper models
  • AI Analysis - Google Gemini API
  • CORS enabled for cross-origin requests

Audio Processing

  • MediaRecorder API - Browser recording
  • FFT Analysis - Frequency domain processing
  • Autocorrelation - Pitch detection
  • RMS Analysis - Volume/loudness calculation
  • Energy Detection - Speech segment identification

🚀 Quick Start

Prerequisites

  • Node.js 18+
  • npm or yarn
  • Modern web browser with MediaRecorder support

Installation

  1. Clone the repository

    git clone https://github.com/Rajukrsna/aiPitchEvaluator.git
cd aiPitchEvaluator

  2. Install frontend dependencies

    npm install

  3. Install backend dependencies

    cd backend
npm install

  4. Environment Setup Create a .env file in the backend directory:

    # Required API Keys
HUGGINGFACE_API_KEY=your_huggingface_token
GEMINI_API_KEY=your_gemini_api_key

# Server Configuration PORT=5000


5. **Get API Keys**
   - **Hugging Face**: Sign up at [huggingface.co](https://huggingface.co) → Settings → Access Tokens
   - **Google Gemini**: Get API key from [Google AI Studio](https://makersuite.google.com/app/apikey)

### Running the Application

1. **Start the backend server**
   ```bash
   cd backend
   npm start

  1. Start the frontend (in a new terminal)

    npm run dev

  2. Open your browser Navigate to http://localhost:5173

📱 How to Use

  1. Record Audio - Click the record button and speak your pitch
  2. Upload & Analyze - Submit your recording for AI analysis
  3. View Results - See detailed scores for delivery and engagement metrics
  4. Get Feedback - Click the lightbulb icons for specific improvement suggestions
  5. Track Progress - All recordings are saved locally for comparison

🎯 Evaluation Metrics

Delivery Analysis

  • Pace - Speaking speed and rhythm
  • Tone - Voice modulation and variety
  • Clarity - Speech intelligibility and pronunciation
  • Confidence - Voice stability and assertiveness
  • Enthusiasm - Energy and engagement level

Engagement Analysis

  • Storytelling - Narrative structure and flow
  • Audience Connection - Relatability and appeal
  • Persuasiveness - Convincing power and impact

🏗️ Project Structure

audiopitchevaluator/
├── src/
│   ├── components/
│   │   ├── Homepage.tsx      # Recording interface
│   │   ├── Dashboard.tsx     # Results dashboard
│   │   └── EvaluationResult.tsx # Score display
│   ├── utils/
│   │   └── audioStorage.ts   # IndexedDB utilities
│   └── main.tsx             # App entry point
├── backend/
│   ├── server.js            # Express API server
│   ├── audioAnalysis.js     # Real audio processing
│   ├── freeTranscription.js # Speech-to-text
│   ├── geminiAnalysis.js    # AI content analysis
│   └── .env                 # Environment variables
└── README.md

🔧 API Endpoints

  • POST /api/evaluate-pitch - Submit audio for analysis
  • GET /api/transcription-methods - Get available transcription options

🎨 UI Features

  • Modern Design - Slate and stone color palette
  • Responsive Layout - Works on desktop and mobile
  • Interactive Elements - Hover effects and smooth transitions
  • Loading States - Visual feedback during processing
  • Error Handling - Graceful error messages and fallbacks

🔒 Privacy & Security

  • Local Storage - Audio files stored in browser IndexedDB
  • No File Uploads - Audio processed locally, only analysis sent to server
  • API Key Security - Environment variables for sensitive data
  • CORS Protection - Configured for secure cross-origin requests

🚀 Deployment

Frontend (Vercel/Netlify)

npm run build
# Deploy the 'dist' folder

Backend (Railway/Heroku)

cd backend
# Set environment variables in your hosting platform
# Deploy with Node.js runtime

🤝 Contributing

  1. Fork the repository
  2. Create a feature branch (git checkout -b feature/amazing-feature)
  3. Commit your changes (git commit -m 'Add amazing feature')
  4. Push to the branch (git push origin feature/amazing-feature)
  5. Open a Pull Request

📝 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

  • Hugging Face - Free speech-to-text models
  • Google Gemini - AI-powered content analysis
  • Lucide - Beautiful icon library
  • Tailwind CSS - Excellent styling framework

📞 Support

If you have any questions or issues, please open an issue on GitHub or contact the maintainers.

Built with ❤️ using React, TypeScript, and AI

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