Extending Embodied Lexical Development
David H. Bailey, Nancy Chang, Jerome A. Feldman, Srini Narayana
Abstract
This paper describes an implemented computational model of lexical development for the case of action verbs. A simulated agent is trained by an informant labeling the agent’s actions (here hand motions), and the system learns to both label and carry out similar actions. The verb learning model is placed in the broader context of the NTL project on embodied natural language and its acquisition. Based on experimental results and projections to the full range of early lexemes, a significantly enriched model is proposed and its properties discussed.
Topics & Concepts
Embodied cognitionLinguisticsComputer sciencePhilosophyArtificial intelligenceNatural Language Processing TechniquesSpeech and dialogue systemsMultimodal Machine Learning Applications