Conceptual alignment in a joint picture-naming task performed with a social robot

• Main Authors: Baus, C. (Author), Cirillo, G. (Author), Nguyen, N. (Author), Runnqvist, E. (Author), Strijkers, K. (Author)
• Format: Article
• Language: English
• Published: Elsevier B.V. 2022
• Subjects: Artificial partner; Conceptual alignment; Joint action; Lexical alignment; Picture naming; Spoken word production
• Online Access: View Fulltext in Publisher

 In this study we investigated whether people conceptually align when performing a language task together with a robot. In a joint picture-naming task, 24 French native speakers took turns with a robot in naming images of objects belonging to fifteen different semantic categories. For a subset of those semantic categories, the robot was programmed to produce the superordinate, semantic category name (e.g., fruit) instead of the more typical basic-level name associated with an object (e.g., pear). Importantly, while semantic categories were shared between the participant and the robot (e.g., fruits), different objects were assigned to each of them (e.g., the object of ‘a pear’ for the robot and of ‘an apple’ for the participant). Logistic regression models on participants' responses revealed that they aligned with the conceptual choices of the robot, producing over the course of the experiment more superordinate names (e.g., saying ‘fruit’ to the picture of an ‘apple’) for those objects belonging to the same semantic category as where the robot produced a superordinate name (e.g., saying ‘fruit’ to the picture of a ‘pear’). These results provide evidence for conceptual alignment affecting speakers' word choices as a result of adaptation to the partner, even when the partner is a robot. © 2022 Elsevier B.V.