Understanding and modeling consumers' stylistic taste such as "sporty" is crucial for creating designs that truly connect with target audiences. However, capturing taste during the design process remains challenging because taste is abstract and subjective, and preference data alone provides limited guidance for concrete design decisions. This paper proposes an integrated human-centered computational framework that links subjective evaluations (e.g., perceived luxury of car wheels) with domain-specific features (e.g., spoke configuration) and computer vision-based measures (e.g., texture). By jointly modeling human-derived (consumer and designer) and machine-extracted features, our framework advances aesthetic assessment by explicitly linking model outcomes to interpretable design features. In particular, it demonstrates how perceptual features, domain-specific design patterns, and consumers' own interpretations of style contribute to aesthetic evaluations. This framework will enable product teams to better understand, communicate, and critique aesthetic decisions, supporting improved anticipation of consumer taste and more informed exploration of design alternatives at design time.

翻译：理解和建模消费者诸如“运动感”等风格品味对于创造真正与目标受众产生共鸣的设计至关重要。然而，在设计过程中捕捉品味仍然具有挑战性，因为品味是抽象且主观的，仅凭偏好数据难以为具体的设计决策提供充分指导。本文提出了一种集成的人本计算框架，该框架将主观评价（例如，对汽车轮毂的奢华感知）与领域特定特征（例如，辐条配置）以及基于计算机视觉的度量（例如，纹理）联系起来。通过联合建模源自人类（消费者和设计师）的特征与机器提取的特征，我们的框架通过将模型结果明确关联到可解释的设计特征，推进了审美评估。具体而言，它展示了感知特征、领域特定的设计模式以及消费者自身对风格的解释如何共同影响审美评价。该框架将使产品团队能够更好地理解、沟通和评判美学决策，从而在设计阶段支持改进对消费者品味的预测，并对设计替代方案进行更明智的探索。