Personalized Audiovisual Compilation With Name-Substituted Team Training
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing training videos in large companies are dull and impersonal due to the broad audience they serve, and creating targeted videos is not feasible, leading to limited impact.
Innovation Solution
An audiovisual compilation tool that personalizes content by substituting audible names for different viewers, blending marked sections with surrounding audio, and adding tracked feedback questions and graphical elements, using machine learning to tailor content to specific teams and individuals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If training videos are designed for a broad audience, then they can serve more employees, but the content becomes dull and impersonal
Solution Approach 1:
The patent segments the training video content into modular components that can be dynamically assembled and personalized for different viewers. Instead of creating separate videos for each employee, the system divides content into reusable segments that are recombined based on individual viewer characteristics, resolving the contradiction between broad coverage and personalization.
Solution Approach 2:
The system changes parameters of the training content dynamically based on viewer characteristics. By adjusting content parameters such as name substitutions, role-specific examples, and personalized greetings, the system maintains broad audience coverage while delivering personalized experiences through parameter modification rather than content creation.
2Ease of manufacture
If training videos are made targeted and personalized, then they become more engaging, but it is not feasible to create separate videos for each employee
Solution Approach 1:
The patent uses copying by creating a single master training video template that can be automatically copied and customized for each employee. The system generates personalized versions through automated text substitution and parameter changes rather than manual video production, maintaining high engagement while ensuring production efficiency.
Solution Approach 2:
The system enables self-service personalization where the training video automatically adapts to each viewer without requiring manual intervention. The automated personalization engine handles name substitutions, role-specific content insertion, and customization based on viewer profiles, eliminating the need for manual video creation for each employee.
3Ease of manufacture
If company officials personally train each employee, then training becomes personalized and effective, but the company cannot afford the resources
Solution Approach 1:
The patent introduces an artificial intelligence system as an intermediary between company officials and employees. This AI mediator delivers personalized training content at scale by analyzing viewer characteristics and automatically customizing content, replacing the need for direct official-employee interaction while maintaining personalization benefits.
Solution Approach 2:
The AI training system performs multiple functions that would otherwise require different resources: it personalizes content, delivers training, tracks progress, and adapts to individual learners all through a single automated platform. This multi-functionality eliminates the need for extensive human resources while maintaining high personalization standards.
Data Source
AI summary
An audiovisual compilation tool is provided for generating a customized and personalized audiovisual compilation. The audiovisual compilation tool receives a request that specifies a purpose and team. Based on the request, the audiovisual compilation personalization tool accesses a candidate viewer data structure to identify candidate viewers on the specified team. The audiovisual compilation tool creates a customized audiovisual compilation based on items of audiovisual content labeled for the specified purpose and based on aggregate characteristics of the candidate viewers. The customized audiovisual compilation is personalized by substituting audible names for different candidate viewers in marked sections of audio from the selected audiovisual content, and blending the marked sections with surrounding audio content. Tracked feedback questions specific to content in the audiovisual compilation may be automatically generated and inserted into the audiovisual compilation, and overlayed graphical elements may be added to trigger external functionality from within the audiovisual compilation.