Computational Design approaches facilitate the generation of typographic design, but evaluating these designs remains a challenging task. In this paper, we propose a set of heuristic metrics for typographic design evaluation, focusing on their legibility, which assesses the text visibility, aesthetics, which evaluates the visual quality of the design, and semantic features, which estimate how effectively the design conveys the content semantics. We experiment with a constrained evolutionary approach for generating typographic posters, incorporating the proposed evaluation metrics with varied setups, and treating the legibility metrics as constraints. We also integrate emotion recognition to identify text semantics automatically and analyse the performance of the approach and the visual characteristics outputs.

翻译：计算设计方法促进了排版设计的生成，但评估这些设计仍是一项具有挑战性的任务。本文提出了一组用于排版设计评估的启发式指标，重点关注可读性（评估文本可见性）、美学性（评估设计的视觉质量）以及语义特征（评估设计传达内容语义的有效程度）。我们采用一种受限进化方法生成排版海报，将所提出的评估指标以不同配置融入其中，并将可读性指标作为约束条件。同时，我们整合情感识别以自动识别文本语义，并分析该方法的性能及输出结果的视觉特征。