MetaDesigner: Advancing Artistic Typography through AI-Driven, User-Centric, and Multilingual WordArt Synthesis

2024-06-28

arXiv.org

AI Summary

To address low visual fidelity, semantic disconnection, and insufficient personalization in multilingual WordArt synthesis, this paper proposes an AI-driven, user-centered generative framework. Methodologically, it introduces a novel LLM-guided tri-agent collaborative architecture—comprising Pipeline, Glyph, and Texture agents—that jointly performs semantic interpretation, glyph modeling, and texture generation. A dual closed-loop mechanism integrating user feedback and multimodal evaluation enables dynamic style-topic iteration and adaptive optimization of design parameters. The framework synergistically combines large language models, prompt engineering, font rendering techniques, and multimodal evaluation models. Experiments demonstrate significant improvements in cross-lingual visual fidelity and contextual consistency; user satisfaction reaches 92.3%, and real-time interactive design is supported. This work establishes a scalable, interpretable paradigm for personalized artistic font generation.

Technology Category

• Natural Language Processing: Code Generation / Program Synthesis from Natural Language
• Humans and AI: Game Design — Procedural Content Generation & Storytelling
• Cognitive Modeling & Cognitive Systems: Computational Creativity

Application Category

• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• User Modeling, Personalization and Recommendation: Large Language Models (LLM) for user modeling and recommendation
• Social Networks and Social Media: Generative AI / large language models and their impact on social systems

Abstract

MetaDesigner introduces a transformative framework for artistic typography synthesis, powered by Large Language Models (LLMs) and grounded in a user-centric design paradigm. Its foundation is a multi-agent system comprising the Pipeline, Glyph, and Texture agents, which collectively orchestrate the creation of customizable WordArt, ranging from semantic enhancements to intricate textural elements. A central feedback mechanism leverages insights from both multimodal models and user evaluations, enabling iterative refinement of design parameters. Through this iterative process, MetaDesigner dynamically adjusts hyperparameters to align with user-defined stylistic and thematic preferences, consistently delivering WordArt that excels in visual quality and contextual resonance. Empirical evaluations underscore the system's versatility and effectiveness across diverse WordArt applications, yielding outputs that are both aesthetically compelling and context-sensitive.

Problem

• AI-driven artistic typography synthesis
• User-centric multilingual WordArt creation
• Iterative refinement of design parameters

Innovation

• LLM-powered typography synthesis
• Multi-agent system orchestration
• Dynamic hyperparameter adjustment