用AI自动推荐搭配美观的中英文字体对，提升设计效率。
AI Based Font Pair Suggestion Modelling For Graphic Design
- 构建字体视觉嵌入与笔画宽度算法，量化字体特征。
- 通过轻量模型和加权评分，从3000+字体中快速推荐配对。
- 适合设计师快速生成符合语境的高质量排版方案。
微软设计器中，为设计建议选择上下文相关且新颖的字体是关键挑战。以往依赖人工将设计意图映射到字体，虽质量高但难以扩展至3000+字体及多种用户意图。本文提出字体视觉嵌入、笔画宽度算法、字体类别-字体映射数据集、基于大语言模型的类别描述生成，以及轻量级低延迟的知识蒸馏微型语言模型（Mini LM V2），用于推荐美观直观的标题与副标题字体组合。结合加权评分机制、最近邻方法和分层采样对字体对进行排序，提升推荐新颖性。
原文摘要 · Abstract (English)
One of the key challenges of AI generated designs in Microsoft Designer is selecting the most contextually relevant and novel fonts for the design suggestions. Previous efforts involved manually mapping design intent to fonts. Though this was high quality, this method does not scale for a large number of fonts (3000+) and numerous user intents for graphic design. In this work we create font visual embeddings, a font stroke width algorithm, a font category to font mapping dataset, an LLM-based category utilization description and a lightweight, low latency knowledge-distilled mini language model (Mini LM V2) to recommend multiple pairs of contextual heading and subheading fonts for beautiful and intuitive designs. We also utilize a weighted scoring mechanism, nearest neighbor approach and stratified sampling to rank the font pairs and bring novelty to the predictions.
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