Document-Driven Multimedia Summary Pages With Harmonized Text-Image Layout

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Solution Overview

Problem

Conventional methods for creating multimedia summary pages are laborious, dependent on user artistic talent, and limited by template options, failing to leverage document content for automatic generation.

Innovation Solution

A summary page generation system that uses generative AI to automatically create diverse, semantically relevant multimedia summary pages by extracting text content and generating harmonized images, employing a Socratic Model framework and text-to-image models to balance text layout and background imagery.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of operation

If conventional methods are used to create multimedia summary pages, then user control over design is maintained, but the process is laborious and dependent on user artistic talent

Engineering Contradiction:

Improveease of creationVSAvoidtime consumption

Core Design Contradiction:

Ease of operationVSLoss of time

Solution Approach 1:

The system enables self-service by automatically generating multimedia summary pages using the document's own content. The language model extracts text content and generates summaries, while text-to-image models create background imagery, allowing the system to serve itself without requiring user artistic talent or manual design input.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

Manual mechanical design processes are replaced with automated AI systems. The language model and text-to-image generative models substitute for human creative work, automatically transforming document content into visually appealing summary pages with harmonized text layouts and background imagery.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Adaptability or versatility

If template-based methods are used, then consistency is maintained, but creativity and semantic relevance are limited

Engineering Contradiction:

Improvesemantic relevanceVSAvoidsystem complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system dynamically changes parameters based on document content. The language model adjusts text extraction and summarization parameters, while text-to-image models adjust background generation parameters, allowing each summary page to be semantically relevant to its specific document rather than constrained by fixed templates.

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The system transitions from static templates to dynamic generation. The harmonization process dynamically adjusts text layout, font styles, sizes, and colors based on the extracted document content, creating adaptable summary pages that respond to the specific semantic characteristics of each document.

Inventive Principle:

Principle #15Dynamics

3Adaptability or versatility

If multiple design options are generated, then diversity is improved, but computing resource consumption increases

Engineering Contradiction:

Improvedesign diversityVSAvoidcomputing resource consumption

Core Design Contradiction:

Adaptability or versatilityVSUse of energy by moving object

Solution Approach 1:

The system applies partial action by generating a focused set of diverse design options rather than exhaustive possibilities. The language model generates targeted text summaries, and text-to-image models generate relevant background imagery, providing sufficient diversity for user selection without excessive computing resource consumption.

Inventive Principle:

Principle #16Partial or excessive action

4Shape

If automatic text-to-image generation is used, then visual appeal is improved, but alignment between text and background may deteriorate

Engineering Contradiction:

Improvevisual compositionVSAvoidtext-background alignment

Core Design Contradiction:

ShapeVSManufacturing precision

Solution Approach 1:

The harmonization process uses feedback to achieve proper alignment. The system iteratively adjusts text layout, font styles, sizes, and colors based on the generated background imagery, ensuring that text and background are visually harmonized while maintaining semantic relevance to the document content.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The system performs preliminary text extraction and summarization before generating background imagery. This preliminary action allows the text content to be prepared and structured in advance, facilitating better alignment and harmonization with the subsequently generated visual elements.

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS20250278875A1Summary page generation using documents

Publication Date: 2025.09.04 ADOBE INC

AI summary

Embodiments are disclosed for summary page generation using a document. The method may include receiving a text document. The method may further include generating a test summary based on the text document and a structured representation of the text summary using the document summarized model. The method may further include generating an image generation prompt based on the text summary and the structured representation of the text summary using a prompt generator. The method may further include generating a multimedia summary document corresponding to the text document using a diffusion model and the image generation prompt. The multimedia summary document includes a generated background imagery based on the text summary. The multimedia summary document includes at least a portion of the text summary which is placed within the multimedia summary document based on the structed representation of the text summary.