A framework for developing adaptive acoustic comfort: Insights from expert interviews

• A framework for adaptive acoustic comfort is developed through expert interviews. • The model proposes a relationship between indoor acoustic perception, outdoor conditions, and adaptation. • Personal, environmental, and building-related variables shape adaptive responses. • A structured data collection process is proposed for model testing. The ability of individuals to adapt to environmental conditions, known as environmental adaptation, reflects their capacity to modify behaviors and physical surroundings to better align with external demands. In thermal comfort assessments, this adaptation process is evaluated using the adaptive thermal comfort model. Similarly, the relationship between individuals’ adaptability and their perception of acoustic environments is also considered to play a significant role in acoustic comfort assessments. Based on this foundation, this study investigates the development and assessment of an adaptive acoustic comfort model, following on its initial definition: “a model that relates indoor acoustic conditions to outdoor ones, moderated by other environmental, contextual, and personal factors.” Through expert interviews, the research aims to develop a preliminary framework for assessing adaptive acoustic comfort, highlighting the importance of environmental adaptation and user tolerance. This framework includes the identification of assessment methods, acoustic indicators, and adaptive model variables necessary for testing the model’s existence and effectiveness in acoustic evaluations. By examining acoustic comfort from an adaptive perspective, the study recommends evaluating indoor acoustic comfort in relation to outdoor conditions. To capture variability in user responses, it suggests having real-world data alongside laboratory studies using specific acoustic indicators. Additionally, the model framework emphasizes the necessity of evaluating personal, environmental, and building-related variables through various developed adaptive models.