AI Commentary Personalization With Virtual Persona Models
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The increase in online live streaming of sporting events has led to viewers opting for additional commentary sources, increasing energy consumption and reducing the appeal of default commentary, as users seek personalized commentary based on their preferences.
Innovation Solution
A system that generates customized commentary using a virtual persona model, processing competition data with AI to mimic the voice, tone, and personality of preferred commentators, allowing users to select personalized commentary based on their interests.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If users select commentary from additional sources to personalize their viewing experience, then user engagement and satisfaction improve, but energy consumption increases due to using multiple devices
Solution Approach 1:
The patent combines multiple commentary functions into a single integrated system that can deliver personalized commentary through the same device used for viewing. The system merges the capabilities of video playback and customized audio commentary delivery, eliminating the need for separate devices and reducing overall energy consumption while maintaining commentary personalization.
Solution Approach 2:
The system implements multi-functionality by enabling a single device to serve both as a video display and as a personalized commentary delivery platform. The commentary system can adapt to different user preferences and deliver customized commentary through the existing device infrastructure, making the device universal for both viewing and personalized audio engagement.
2Adaptability or versatility
If traditional live streaming commentary is provided, then implementation simplicity is maintained, but user engagement decreases due to lack of personalization
Solution Approach 1:
The system performs preliminary actions by pre-configuring virtual persona models and commentary templates before user interaction. User preferences are captured in advance, and personalized commentary streams are prepared beforehand, allowing the system to deliver customized commentary without requiring complex real-time processing during live events.
Solution Approach 2:
The patent uses virtual persona models that replicate the speaking styles, tones, and characteristics of real commentators. These digital copies enable personalized commentary delivery without requiring actual human commentators for each user, thus achieving high adaptability while controlling system complexity through automated synthesis rather than manual coordination.
3Adaptability or versatility
If multiple independent streamers provide commentary, then commentary diversity increases, but the appeal of default commentary decreases and users seek alternative sources
Solution Approach 1:
The system implements dynamic adaptability by allowing users to select and switch between different virtual persona models based on their preferences. The commentary delivery is dynamically adjusted to match user-selected personas, maintaining the appeal of default commentary through customizable options rather than static, one-size-fits-all approaches.
Solution Approach 2:
The patent enables commentary customization by allowing users to modify parameters such as commentator voice, tone, style, and subject matter focus. These parameter changes transform the default commentary into personalized content, maintaining user engagement with the default stream while providing the versatility of customized commentary options.
Data Source
AI summary
Systems and methods are described for producing customized commentary. Data relating to a competition activity is received. Information relating to at least one event occurring during the competition activity is inferred by processing the data using an artificial intelligence model. The information relating to at least one event is processed using a virtual persona model to generate customized commentary. The customized commentary is output.