In this paper we propose a trainable system that learns grounded language models from examples with a minimum of user intervention and without feedback. We have focused on the acquisition of grounded meanings of spatial and adjective/noun terms. The system has been used to understand and subsequently to generate appropriate natural language descriptions of real objects and to engage in verbal interactions with a human partner. We have also addressed the problem of resolving eventual ambiguities arising during verbal interaction through an information theoretic approach.
|Numero di pagine||7|
|Stato di pubblicazione||Published - 2009|
All Science Journal Classification (ASJC) codes
- Artificial Intelligence
- Human-Computer Interaction