Personalized Summary Video Generation for Multi-Event Highlight Selection
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Solution Overview
Problem
Traditional systems for selecting media samples from multi-sport, multi-day events are cumbersome, time-consuming, and impersonal, leading to low viewership and returning customers.
Innovation Solution
Employing AI techniques to generate personalized summary videos based on user preferences and personal data, integrating a subset of media samples and voiceovers, with optional human auditing to produce digestible and engaging content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional manual selection methods are used to choose media samples, then observers can select individual media samples of interest, but the process becomes cumbersome, time-consuming, and inefficient
Solution Approach 1:
The system performs automatic media sample selection itself without requiring user intervention. The AI system analyzes user preferences, event data, and media metadata to autonomously curate and assemble personalized highlight reels, eliminating the manual selection process entirely
Solution Approach 2:
The patent replaces the manual mechanical process of selecting media samples with an automated AI-based system. Machine learning algorithms process and analyze data to automatically select and assemble media samples, substituting human manual operations with automated computational processes
2Productivity
If traditional impersonal applications are used, then media samples can be delivered to users, but viewership and returning customers remain relatively low
Solution Approach 1:
The system customizes the media content specifically for each individual user based on their unique preferences, viewing history, and personal data. Each user receives a personalized highlight reel tailored to their specific interests rather than a generic uniform content delivery
Solution Approach 2:
The system dynamically adapts the media content based on real-time user preferences and behavior. The AI continuously learns from user interactions and adjusts the personalized content accordingly, making the system flexible and responsive to changing user needs
3Quantity of substance
If comprehensive media coverage is provided for multi-sport events, then observers have access to extensive media samples, but the vast number of samples makes selection and loading cumbersome
Solution Approach 1:
The AI system extracts only the most relevant and important media samples from the vast available pool. It identifies and pulls out key highlights and essential content based on user preferences, eliminating the need for users to navigate through unnecessary media samples
Solution Approach 2:
Instead of presenting all available media samples, the system applies partial action by selecting only a curated subset of the most valuable content. This selective approach provides sufficient coverage without overwhelming the user with excessive media samples
Data Source
AI summary
A computer-implemented includes determining, via processing circuitry, user preference data relating to a user and a television or streaming event. The computer-implemented method also includes determining, via the processing circuitry and based on the user preference data, a sub-set of media samples from a plurality of media samples stored in a database system and corresponding to the television or streaming event. The computer-implemented method also includes determining, via the processing circuitry, personal data indicative of the user. The computer-implemented method also includes generating, via the processing circuitry, based on generative Artificial Intelligence (GenAI) techniques, and based on the personal data, a summary video voiceover. The computer-implemented method also includes generating, via the processing circuitry, a summary video of the television or streaming event, the summary video comprising the sub-set of media samples and the summary video voiceover.