Scalable Automated Dubbing and Video Editing System
Engineered a scalable system for automated speech-to-speech dubbing and video editing based on customizable templates, featuring multi-provider AI integration and automated social media publishing.
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About this project
Engineered a comprehensive scalable system for automated speech-to-speech dubbing and video editing based on customizable templates, designed to handle large-scale video processing workflows.
The platform encompasses multiple technical components working seamlessly together:
Scalable Cloud Architecture
Developed a highly scalable cloud architecture utilizing AWS Fargate for containerized workloads and AWS Lambda for event-driven processing, ensuring both cost efficiency and easy scaling. This architecture supports on-demand scaling of processing tasks, handling varying workloads efficiently.
Multi-Provider AI Integration
Implemented Multi-Provider Integration to support heterogeneous AI services, including TTS (Text-to-Speech) and STT (Speech-to-Text), leveraging providers such as AWS and Google Cloud. This multi-provider approach ensures redundancy, flexibility, and optimal performance.
AI-Powered Speech-to-Speech Dubbing
Designed the core dubbing mechanism to convert source speech to target speech while maintaining natural intonation and voice preservation. The system automatically converts source speech to a target language, preserving natural intonation and voice characteristics.
Automated Video Post-Processing
Automated video post-processing by applying template-based video editing to synchronize dubbed audio accurately with video content. This ensures seamless integration of dubbed audio with the original video footage.
Multi-Platform Publishing & Proxy Management
Managed and orchestrated complex downstream processes, including multi proxy-acc-auto upload social tasks to platforms like YouTube, Facebook, and TikTok. Proxy management capabilities were integrated to handle these operations, enabling native buy, manage, and extend proxies directly within the platform.
Service Health Monitoring
Integrated a Service Health Monitor to track real-time service health, operational logs, and task statistics for essential components like download_tasks_manager and video_processing_tasks_manager. A dedicated dashboard tracks the live status, heartbeats, and logs of all system services.
User Interface & Task Management
Developed the user interface to manage video dubbing tasks, handle mass video imports via URL (e.g., Douyin links), and enable side-by-side comparison of original and translated subtitles. The system supports bulk video processing from URLs, allowing users to ingest and process multiple videos simultaneously.
Key Highlights
- Engineered scalable cloud architecture using AWS Fargate and Lambda for cost-efficient, on-demand scaling
- Implemented multi-provider AI integration supporting AWS and Google Cloud TTS/STT services
- Developed AI-powered speech-to-speech dubbing preserving natural intonation and voice characteristics
- Automated video post-processing with template-based editing for accurate audio-video synchronization
- Integrated multi-platform publishing to YouTube, Facebook, and TikTok with proxy management
- Built real-time service health monitoring dashboard tracking system status, heartbeats, and logs
- Designed user interface supporting bulk video imports via URL and side-by-side subtitle comparison