Paper: Learning Language from Perceptual Context

ACL ID E12-1061
Title Learning Language from Perceptual Context
Venue Annual Meeting of The European Chapter of The Association of Computational Linguistics
Session Main Conference
Year 2012

Machine learning has become the dominant approach to building natural-language processing sys- tems. However, current approaches generally require a great deal of laboriously constructed human- annotated training data. Ideally, a computer would be able to acquire language like a child by being exposed to linguistic input in the context of a relevant but ambiguous perceptual environment. As a step in this direction, we have developed systems that learn to sportscast simulated robot soccer games and to follow navigation instructions in virtual environments by simply observing sample hu- man linguistic behavior in context. This work builds on our earlier work on supervised learning of semantic parsers that map natural language into a formal meaning representation. In order to apply such metho...