Text-to-Image Reading Interaction for Long-Form Content Engagement
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Solution Overview
Problem
Users often lose concentration during long reading sessions due to monotonous text, leading to a poor reading experience and reduced interaction with the content.
Innovation Solution
An interaction method that generates images based on read text, allowing users to watch delivery content and automatically generate images without manual summarization, enhancing user interaction and engagement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If users read long text content continuously, then reading completion rate is improved, but user concentration and reading experience deteriorate
Solution Approach 1:
The system dynamically transforms static text content into dynamic visual images based on user interaction and reading progress. The image generation is not static but evolves as users read different portions of the text, creating a dynamic reading experience that adapts to user engagement levels and maintains concentration over long reading sessions.
Solution Approach 2:
The patent transitions from one-dimensional text reading to two-dimensional visual image perception. By converting text descriptions into generated images, the system adds a visual dimension to the reading process, making long text content more engaging and easier to process, thereby maintaining user concentration throughout.
2Measurement precision
If users manually summarize feature information to generate images, then image generation accuracy is improved, but user workload and operation complexity increase
Solution Approach 1:
The system performs self-service by automatically extracting feature information from the text content and using it to generate images without requiring manual user intervention. The model itself identifies and extracts the necessary feature information, eliminating the need for users to manually summarize while maintaining generation accuracy.
Solution Approach 2:
The patent replaces the mechanical process of manual feature extraction and summarization with an automated AI model. Instead of users manually analyzing text and extracting features, the system uses machine learning models to automatically identify and extract feature information, substituting human cognitive labor with automated computational processes.
3Manufacturing precision
If users understand and summarize feature information manually, then image matching quality is improved, but interaction time and complexity increase
Solution Approach 1:
The system performs preliminary action by pre-extracting and storing feature information from text content before image generation is requested. The model prepares the feature extraction in advance, so when users want to generate an image, the feature information is already available, eliminating the need for users to spend time on manual summarization and analysis.
Solution Approach 2:
The patent replaces the time-consuming manual process of understanding and summarizing feature information with automated machine learning models. The system automatically comprehends the text content and extracts relevant features, substituting human cognitive processing with automated computational analysis, thereby significantly reducing interaction time while maintaining matching quality.
Data Source
AI summary
The present disclosure relates to an interaction method, a non-transitory computer-readable storage medium, and an electronic device, the method includes: displaying a target delivery content in response to receiving, during a display process of a text, an image generation instruction associated with delivery content; acquiring a target text corresponding to the image generation instruction from the text in response to determining that display of the target delivery content is completed; generating target feature information of a target object corresponding to the target text according to the target text; and generating a generated image corresponding to the target object according to the target feature information and displaying the generated image.