|Title||Using spoken words to guide open-ended category formation|
|Author(s)||Chauhan, Aneesh; Seabra Lopes, Luís|
|Source||Cognitive Processing 12 (2011)4. - ISSN 1612-4782 - p. 341 - 354.|
|Publication type||Refereed Article in a scientific journal|
|Keyword(s)||Embodied agents Conceptual development - Human-Robot interaction - Instance-based learning - Object categories - Open-ended category learning - Social language grounding - Vocabulary acquisition - Word categories|
Naming is a powerful cognitive tool that facilitates categorization by forming an association between words and their referents. There is evidence in child development literature that strong links exist between early word-learning and conceptual development. A growing view is also emerging that language is a cultural product created and acquired through social interactions. Inspired by these studies, this paper presents a novel learning architecture for category formation and vocabulary acquisition in robots through active interaction with humans. This architecture is open-ended and is capable of acquiring new categories and category names incrementally. The process can be compared to language grounding in children at single-word stage. The robot is embodied with visual and auditory sensors for world perception. A human instructor uses speech to teach the robot the names of the objects present in a visually shared environment. The robot uses its perceptual input to ground these spoken words and dynamically form/organize category descriptions in order to achieve better categorization. To evaluate the learning system at word-learning and category formation tasks, two experiments were conducted using a simple language game involving naming and corrective feedback actions from the human user. The obtained results are presented and discussed in detail.