Paper: Intentional Context In Situated Natural Language Learning

ACL ID W05-0614
Title Intentional Context In Situated Natural Language Learning
Venue International Conference on Computational Natural Language Learning
Session Main Conference
Year 2005
Authors

Natural language interfaces designed for situationally embedded domains (e.g. cars, videogames) must incorporate knowledge about the users’ context to address the many ambiguities of situated language use. We introduce a model of situated language acquisition that operates in two phases. First, intentional context is represented and inferred from user actions using probabilistic context free grammars. Then, utterances are mapped onto this representation in a noisy channel framework. The acquisition model is trained on unconstrained speech collected from subjects playing an interactive game, and tested on an understanding task.