Why Verbs are Harder to Learn than Nouns: Initial Insights from a Computational Model of Intention Recognition in Situated Word Learning
Michael Fleischman · 2005
We present a computational model that uses intention recognition as a basis for situated word learning. In an initial experiment, the model acquired a lexicon from situated natural language collected from human participants interacting in a virtual game environment. Similar to child language learning, the model learns nouns faster than verbs.