📚 Technology Stack
Python, Next.js, AWS, Stripe, Tailwind CSS, TypeScript, Modal, Inngest, FFmpeg, PyTorch, Whisper AI, LangChain, Redis, Docker
📃 Overview
Duration: 6/2024 - now (oncoming 🚀)
AI Podcast Clipper is a cutting-edge tool that transforms long-form podcast content into highly engaging short-form video clips optimized for social media platforms. Using a sophisticated AI pipeline, the system analyzes audio and video content to identify the most compelling moments, handles speaker detection and face tracking, and produces professional-quality clips ready for immediate distribution on platforms like YouTube Shorts, TikTok, and Instagram Reels.
🧠 AI Models & Capabilities
- Speech Recognition: Whisper AI implementation for accurate transcription across multiple languages and accents
- Semantic Analysis: Fine-tuned transformer models to identify engaging topics, humor, controversies, and valuable insights
- Emotional Detection: Audio analysis for speaker excitement, intensity, and emotional peaks
- Face Detection & Tracking: Computer vision algorithms to identify and follow active speakers
- Smart Cropping: Dynamic framing adjustment based on speaker position and movement
- Content Classification: Automatic tagging and categorization of clip topics and themes
- Engagement Prediction: ML model trained on viral content patterns to prioritize high-potential moments
🎬 Video Processing Pipeline
- Media Ingestion: Support for various input formats including MP4, MOV, MP3 with video reconstruction
- Parallel Processing: Distributed computation for handling multiple podcast episodes simultaneously
- Automatic Chunking: Intelligent segmentation of long-form content into optimal clip lengths
- Visual Enhancement: Color correction, stabilization, and resolution optimization
- Text Overlay: Automatic caption generation with customizable styles and positioning
- Multi-format Export: Dimension and aspect ratio optimization for different platforms (9:16, 1:1, 16:9)
- Thumbnail Generation: AI-selected preview frames with engagement-optimized composition
🛠️ Technical Architecture
- Serverless Compute: Modal.com integration for scalable, on-demand processing
- Background Jobs: Inngest for reliable workflow orchestration and job management
- Cloud Storage: AWS S3 for secure media storage with intelligent lifecycle policies
- Caching Layer: Redis implementation for performance optimization
- Containerized Processing: Docker-based video processing for consistent environments
- API Design: RESTful endpoints with GraphQL integration for flexible data retrieval
- Webhook System: Event-driven architecture for third-party integrations
- Monitoring: Comprehensive logging and performance metrics for ML model evaluation
👤 User Experience
- Intuitive Dashboard: Clean interface for project management and clip monitoring
- Drag-and-Drop Upload: Frictionless content submission process
- Real-time Processing Updates: Live progress indicators during clip generation
- Preview & Editing: Browser-based review with fine-tuning capabilities
- Custom Branding: Logo insertion, color themes, and visual identity options
- Batch Processing: Queue multiple episodes for sequential processing
- Sharing Integration: Direct publishing to connected social media accounts
- Analytics Dashboard: Performance tracking of published clips with engagement metrics
💼 Business & Monetization
- SaaS Subscription Model: Tiered pricing based on processing minutes and features
- Stripe Integration: Secure payment processing with subscription management
- Usage Analytics: Detailed reporting on processing time and resource utilization
- Team Collaboration: Multi-user access with role-based permissions
- White Label Option: Enterprise solution for podcast networks and media companies
- API Access: Developer integration options for custom workflows
🚀 Future Development
- Integration with podcast hosting platforms for direct episode access
- Advanced style transfer for visual customization of clips
- Audience sentiment analysis from comments to refine clip selection algorithm
- Multi-language support with automatic translation overlays
- AI-generated B-roll insertion for enhanced visual engagement
- Collaborative editing features for team environments
- Mobile application for on-the-go clip management
This project demonstrates the powerful intersection of AI, media processing, and content optimization, providing creators with an invaluable tool to expand their audience reach through strategic repurposing of long-form content.