Screen Reader NLP Content Conversion
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Solution Overview
Problem
Natural Language Processing (NLP) systems face difficulties in converting diverse document formats, especially those containing diagrams and images, leading to important content being discarded or requiring costly and time-consuming converter development for each format.
Innovation Solution
A method that utilizes a screen reader application to convert screen views of document sections into natural language format, merging compatible and incompatible sections using native converters and screen reader outputs, respectively, to create a unified NLP format for NLP operations like QA systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If diagrams and images are converted to textual format using native converters, then the content can be processed by NLP systems, but the conversion accuracy and semantic interpretation deteriorate
Solution Approach 1:
The patent introduces an intermediary component (image-to-text conversion service) that specializes in converting visual content to textual format. This intermediary handles the complex task of diagram and image conversion, allowing the native converters to focus on their strengths while still achieving accurate semantic interpretation through the intermediary's specialized capabilities
Solution Approach 2:
The conversion process is segmented into different pathways: native converters handle text-compatible formats while a specialized image-to-text service handles diagrams and images. This segmentation allows each converter to optimize for its specific content type, improving overall conversion accuracy without requiring a single universal converter
2Measurement precision
If a new converter is written for each type of diagram and content format, then conversion accuracy improves, but the system complexity and development time increase
Solution Approach 1:
The patent implements a universal conversion system where a single image-to-text service handles multiple types of visual content (diagrams, images, charts). This multi-functional approach eliminates the need for separate converters for each content type, reducing system complexity while maintaining conversion accuracy through the unified service
3Productivity
If diagrams and images are ignored during conversion, then the conversion process becomes simpler and faster, but important content is discarded
Solution Approach 1:
The system performs preliminary identification of content types before conversion. By detecting whether content is text-compatible or visual early in the process, the system can route it to the appropriate converter, ensuring important visual content is not discarded while maintaining efficient processing through pre-planned conversion pathways
Data Source
AI summary
An approach is provided to make content available to natural language processing (NLP) tasks. In the approach, a screen view of a document section is provided as input to a screen reader application. The screen reader application converts information displayed on the screen into a natural language format. A NLP operation is then performed on the natural language format.