Using spoken words to guide open-ended category formation

Aneesh Chauhan*, Luís Seabra Lopes

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

20 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)341-354
Number of pages14
JournalCognitive Processing
Volume12
Issue number4
DOIs
Publication statusPublished - 4 Nov 2011
Externally publishedYes

Keywords

  • Embodied agents Conceptual development
  • Human-Robot interaction
  • Instance-based learning
  • Object categories
  • Open-ended category learning
  • Social language grounding
  • Vocabulary acquisition
  • Word categories

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