Learning words from sights and sounds: a computational model
Learning words from sights and sounds: a computational model
Grounding knowledge in sensors: unsupervised learning for language and planning
Grounding knowledge in sensors: unsupervised learning for language and planning
Tailoring the Interpretation of Spatial Utterances for Playing a Board Game
AIMSA '08 Proceedings of the 13th international conference on Artificial Intelligence: Methodology, Systems, and Applications
A dialogue approach to learning object descriptions and semantic categories
Robotics and Autonomous Systems
Interactive Learning of Spoken Words and Their Meanings Through an Audio-Visual Interface
IEICE - Transactions on Information and Systems
Rapidly deploying grammar-based speech applications with active learning and back-off grammars
SIGdial '08 Proceedings of the 9th SIGdial Workshop on Discourse and Dialogue
Handling out-of-grammar commands in mobile speech interaction using backoff filler models
SLP '07 Proceedings of the Workshop on Grammar-Based Approaches to Spoken Language Processing
A robot learns to know people: first contacts of a robot
KI'06 Proceedings of the 29th annual German conference on Artificial intelligence
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Communicating by voice with speech-enabled computer applications based on preprogrammed rule grammers suffers from constrained vocabulary and sentence structures. Deviations from the allowed language result in an unrecognized utterance that will not be understood and processed by the system. One way to alleviate this restriction consists in allowing the user to expand the computer's recognized and understood language by teaching the computer system new language knowledge. We present an adaptive dialog system capable of learning from users new words, phrases and sentences, and their corresponding meanings. User input incorporates multiple modalities, including speaking, typing, pointing, drawing, and image capturing. The allowed language can thus be expanded in real time by users according to their preferences. By acquiring new language knowledge the system becomes more capable in specific tasks, although its language is still constrained.