Synchronized Accessibility Content Delivery with AI-Generated Sign Language
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Solution Overview
Problem
Existing solutions for delivering accessibility-enhanced content, particularly for deaf and hearing-impaired individuals, are inefficient and inconvenient, often relying on human sign language translators who struggle to capture emotional intensity and emphasis, and lack scalable automation.
Innovation Solution
A system utilizing machine learning models to synchronize sign language performances or video tokens with primary content, providing accessibility enhancements through automated systems that include sign language interpretations, facial expressions, and haptic effects, which can be delivered via integrated or separate communication channels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If human sign language translators are used, then emotional intensity and emphasis can be captured, but cost increases and scalability is limited
Solution Approach 1:
The patent uses AI-generated virtual sign language avatars that copy and replicate the behaviors of human sign language translators. These virtual performers can be trained on datasets of human sign language performances to reproduce gestures, facial expressions, and emotional nuances, providing scalable accessibility without the cost and availability constraints of human translators.
Solution Approach 2:
The patent replaces the mechanical system of human translators with an automated AI-based system. Machine learning models process audio content and automatically generate synchronized sign language performances, eliminating the need for human intervention while maintaining emotional expression and emphasis through sophisticated gesture synthesis.
2Measurement precision
If human sign language translators are used, then translation accuracy is maintained, but convenience and practicality deteriorate
Solution Approach 1:
The system provides self-service by automatically generating and synchronizing sign language performances with audio content without requiring human translators. The AI system independently processes audio files, generates appropriate gestures and expressions, and synchronizes everything automatically, making the process convenient and accessible while maintaining translation accuracy through trained machine learning models.
3Productivity
If automated systems are implemented, then scalability and efficiency improve, but ability to capture emotional intensity worsens
Solution Approach 1:
The patent applies parameter changes by training AI models on diverse datasets that capture the full range of human emotional expressions and gestures. The system adjusts parameters such as gesture speed, facial expression intensity, and body language to match the emotional tone of the audio content, enabling automated systems to reliably capture emotional intensity while maintaining high efficiency and scalability.
Data Source
AI summary
A system for delivering accessibility enhanced content includes a computer server having processing hardware and a memory storing a software code. The processing hardware is configured to execute the software code to deliver, to a user system, accessibility enhanced content comprising primary content and an accessibility track synchronized to the primary content, the accessibility track including at least one of a sign language performance, or one or more video tokens each expressing one or more words. When the accessibility track includes the sign language performance, the sign language performance is delivered contemporaneously with delivery of the primary content. When the accessibility track includes the one or more video tokens, the one or more video tokens are played back when the primary content reaches a location corresponding to each of the one or more video tokens.