3

Elevenlabs Clone

A full-stack AI text-to-speech platform with voice conversion and audio generation capabilities, implementing three state-of-the-art AI models (StyleTTS2, Seed-VC, and Make-An-Audio) with containerized inference endpoints.

GitHub Website

📚 Technology Stack

PyTorch, Next.js 15, AWS (S3, EC2), Inngest, FastAPI, React, Tailwind CSS, Docker, TypeScript, PostgreSQL, Redis, Prisma, Auth.js, WebAssembly

📃 Overview

Duration: 6/2024 - now (oncoming 🚀)

This project is a sophisticated clone of ElevenLabs' voice AI platform, featuring text-to-speech, voice conversion, and audio generation capabilities. The system self-hosts three state-of-the-art AI models that can be fine-tuned to specific voices, offering users a powerful toolkit for audio content creation. The architecture combines a high-performance Python/PyTorch AI backend with a modern Next.js frontend, all orchestrated through containerized services and efficient queue management.

🧠 AI Models Implementation

  • StyleTTS2: Implementation of a state-of-the-art text-to-speech model capable of generating natural-sounding speech with control over style, prosody, and emotion
  • Seed-VC: Voice conversion model that transforms one person's voice into another while preserving speech content and enhancing naturalness
  • Make-An-Audio: Generative audio model for creating realistic environmental sounds, music, and effects from textual descriptions
  • Fine-tuning Pipeline: Custom training workflow for adapting models to new voices using minimal sample data
  • Inference Optimization: ONNX runtime conversion and quantization techniques for faster generation
  • Voice Cloning: System for creating digital voice replicas from short audio samples
  • Emotion Control: Parameters for adjusting emotional tone and intensity in generated speech

🏗️ System Architecture

  • Microservices Design: Containerized AI models with independent scaling capabilities
  • Asynchronous Processing: Queue-based architecture using Inngest for handling compute-intensive tasks
  • FastAPI Backend: High-performance API endpoints for model inference with automatic documentation
  • Next.js Frontend: Server-side rendering and React Server Components for optimal performance
  • S3 Integration: Scalable storage solution for audio files with secure access controls
  • Database Layer: PostgreSQL for structured data with Prisma ORM for type-safe queries
  • Caching Strategy: Redis implementation for frequently accessed data and inference results
  • Authentication Flow: Secure user management with JWT and Auth.js integration
  • Credit System: Database-backed usage tracking and quota management

🎧 Audio Processing Features

  • Real-time Preview: Low-latency audio previews before final generation
  • Batch Processing: Support for processing multiple text inputs or audio files simultaneously
  • Audio Editing: Waveform visualization with trimming, splitting, and combining capabilities
  • Format Conversion: Support for multiple audio formats (WAV, MP3, OGG, FLAC)
  • Voice Library: Management system for saved and favorited voices
  • Audio Enhancement: Post-processing filters for noise reduction and quality improvement
  • Pronunciation Controls: Custom dictionary and phoneme adjustment for accurate speech
  • Speech Parameters: Adjustable settings for pitch, speed, pauses, and emphasis

💻 Technical Implementation

  • Docker Containerization: Isolated environments for each AI model with resource controls
  • GPU Acceleration: CUDA optimization for PyTorch models with fallback to CPU
  • API Versioning: Structured API evolution with backward compatibility
  • Streaming Response: Chunked audio delivery for improved user experience during generation
  • WebSocket Integration: Real-time progress updates during processing
  • Background Workers: Dedicated processing threads for handling intensive computations
  • Error Handling: Comprehensive error tracking and graceful degradation
  • Monitoring: Prometheus metrics for system performance and model behavior

👤 User Experience & Interface

  • Intuitive Dashboard: Clean, responsive interface for all audio generation tasks
  • Voice Management: Tools for creating, editing, and organizing voice profiles
  • Project Organization: Folder structure for managing related audio generations
  • History & Favorites: Access to past generations with search and filtering
  • Credit Usage Visibility: Clear display of resource consumption and limits
  • Audio Playback: In-browser player with visualization and controls
  • Responsive Design: Optimized experience across desktop and mobile devices
  • Theme Support: Light and dark mode with customizable accent colors

🛡️ Security & Compliance

  • Data Encryption: End-to-end encryption for user audio data
  • Access Controls: Role-based permissions for team environments
  • Usage Limits: Rate limiting and quota enforcement to prevent abuse
  • Content Moderation: Filters for preventing misuse of voice generation
  • Privacy Settings: User controls for data retention and sharing
  • Audit Logging: Comprehensive tracking of system actions and access

🔮 Future Development

  • Integration with content creation platforms (YouTube, podcast hosts)
  • Advanced voice editing with multi-track mixing capabilities
  • Real-time voice conversion for live applications
  • Additional language support beyond English
  • Mobile application with offline processing capabilities
  • API marketplace for developers to integrate voice capabilities

This project demonstrates advanced skills in AI model deployment, full-stack development, and cloud infrastructure, creating a powerful alternative to commercial text-to-speech platforms with enhanced customization capabilities.