Voice-Guided Screen Summarization and Text Editing for Accessibility
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Solution Overview
Problem
Visually impaired individuals face significant barriers in efficiently acquiring information from electronic device screens and performing text input or editing operations due to the limitations of conventional voice-based systems in providing concise summaries, flexible text editing, and comprehensive email creation through intuitive voice commands, leading to reduced independence and productivity.
Innovation Solution
A system comprising a processor that acquires and analyzes voice commands, obtains relevant screen information, and utilizes a generative artificial intelligence model to summarize or edit content, delivering the results through synthesized speech, enabling efficient text-based task management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional voice-based systems are used for information access and text operations, then visual impairment accessibility is improved, but information acquisition efficiency and task management capability deteriorate
Solution Approach 1:
The patent replaces conventional mechanical voice command recognition with an AI-based natural language processing system. The processor uses machine learning models to understand and interpret user intent from spoken language, enabling more efficient and accurate information retrieval and text manipulation operations compared to traditional keyword-based voice systems.
Solution Approach 2:
The system dynamically adjusts information presentation parameters based on user needs. The processor analyzes context and user preferences to modify output format, detail level, and presentation mode, optimizing both accessibility and efficiency for visually impaired users performing various tasks.
2Loss of information
If detailed screen information is provided to visually impaired users, then information completeness is improved, but information processing time and cognitive load increase
Solution Approach 1:
The patent segments screen information into hierarchical levels of detail. The processor divides complex screen content into structured components (headings, paragraphs, key elements) and allows users to access information at different granularities, presenting only relevant portions based on current task context to reduce processing time while maintaining completeness when needed.
Solution Approach 2:
The system implements partial information delivery by providing summaries and key points first, then offering detailed information on demand. This approach delivers sufficient information for most tasks without overwhelming users with complete detail, reducing processing time while maintaining the ability to access full information when required.
3Adaptability or versatility
If comprehensive text editing capabilities are provided, then task functionality is improved, but system complexity increases
Solution Approach 1:
The patent implements a universal voice-based text editing system where a single AI-powered processor handles multiple editing operations (selection, copying, pasting, deletion, formatting) through natural language commands. This multi-functional approach provides comprehensive text editing capabilities without requiring separate specialized systems for each operation, managing complexity through unified AI processing.
4Ease of operation
If voice commands are made more intuitive and natural, then ease of use is improved, but recognition accuracy and processing reliability may deteriorate
Solution Approach 1:
The patent implements feedback mechanisms where the system confirms interpreted commands before execution and provides clarification when recognition confidence is low. The processor analyzes speech patterns and context, then validates understanding by presenting interpreted commands to users for confirmation, maintaining high reliability while accepting natural, varied speech inputs.
Solution Approach 2:
The system performs preliminary speech analysis and context preparation before final command execution. The processor pre-processes spoken input by analyzing acoustic features, comparing against known command patterns, and preparing multiple interpretation options, then selects the most accurate interpretation to maintain reliability while accepting intuitive natural speech.
Data Source
AI summary
A system includes a processor that is configured to acquire a voice command from a user, analyze the acquired voice command, acquire screen information based on the analyzed voice command, process the acquire screen information using a generative artificial intelligence model to summarize or edit the information, and provide the summarized or edited information to the user as synthesized speech.


