AI-Powered Speech-to-Text Web App

Built a full-stack Laravel application that captures audio from the browser, offloads it to a queue, transcribes it using OpenAI's Whisper API, and delivers real-time transcription results via WebSockets. This project demonstrated proficiency in backend architecture, queue management, real-time communication, and seamless integration with AI APIs.

Key Features

• Audio Capture: Browser-based audio recording functionality for seamless user experience
• Queue Management: Efficient background processing of audio files using Laravel queues
• AI Integration: Seamless integration with OpenAI's Whisper API for accurate speech transcription
• Real-time Updates: WebSocket implementation for instant delivery of transcription results
• Performance Optimization: FrankenPHP for enhanced PHP application performance
• Scalable Architecture: Built with modern PHP practices for scalability and maintainability

Technical Architecture

• Framework: Laravel for robust backend development
• Runtime: FrankenPHP for high-performance PHP execution
• Real-time Communication: WebSockets for instant result delivery
• Queue System: Laravel queues for asynchronous audio processing
• AI Service: OpenAI Whisper API for speech-to-text transcription
• Frontend: JavaScript for audio capture and real-time updates

Project Highlights

• Modern Tech Stack: Utilized cutting-edge technologies including FrankenPHP and WebSockets
• AI-Powered: Leveraged OpenAI's advanced Whisper API for accurate transcription
• Real-time Experience: Implemented WebSocket communication for immediate result delivery
• Scalable Design: Built with queue-based architecture to handle multiple concurrent requests
• Full-stack Solution: Comprehensive application covering frontend audio capture to backend processing

Project Timeline

Duration: August 2025 - Present

This project showcases expertise in modern web development, AI integration, real-time communication, and scalable backend architecture using the latest PHP technologies.