Machine-Learning Assisted Personalized Real-Time Video Editing and Playback

Smart overview of the Invention

This invention outlines a system for personalized, real-time video editing and playback using machine learning. Users can choose content, and the system analyzes their preferences to edit the video dynamically. It allows real-time user interaction through text or voice commands during playback, providing a customized viewing experience tailored to individual tastes.

Field of Application

The invention falls under multimedia content editing and playback, utilizing machine learning and AI to offer personalized video experiences. Key classifications include machine learning in video processing, personalized content delivery, and user modeling for tailored content.

Background

With the rise of on-demand video services, users face challenges in finding content that matches their specific interests. Current systems lack real-time personalization capabilities. This invention fills that gap by allowing users to modify video content dynamically during playback, based on direct commands.

System Components

• Machine Learning Module: Processes user preferences and metadata.
• Content Filtering Engine: Edits video content in real-time.
• Playback System: Delivers personalized videos to devices.
• User Interface: Allows input via text or voice commands.

Functionality

Users select content from a platform, and the system loads any existing preferences. They can set new rules or make real-time requests to tailor the video experience. The system processes these requests using metadata and machine learning to edit the content accordingly, offering a seamless and engaging viewing experience.