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Conference papers
On-Line Learning of Lexical Items and Grammatical Constructions via Speech, Gaze and Action-Based Human-Robot Interaction
Abstract : In order to be able to understand a conversation in interaction, a robot, has to first understand the language used by his interlocutor. A central aspect of language learning is adaptability. Individuals can learn new words and new grammatical structures. We have developed learning methods that allow the hu-manoid robot iCub to robot can learn new lexical items by interaction with the human and consolidation of its autobiographical memory. Then, based on these open class words, the robot can bootstrap the acquisition of novel grammatical structures in real-time. Finally, we demonstrate how human gaze can be monitored, and could be used in order to reduce referential ambiguity inherent in such learning conditions. These learning capabilities are demonstrated in a collection of videos.
Cited literature [13 references]
https://hal.inria.fr/hal-02561340
Contributor : Xavier Hinaut <>
Submitted on : Sunday, May 3, 2020 - 6:48:08 PM
Last modification on : Friday, December 18, 2020 - 8:36:03 PM
Contributor : Xavier Hinaut <>
Submitted on : Sunday, May 3, 2020 - 6:48:08 PM
Last modification on : Friday, December 18, 2020 - 8:36:03 PM
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Pointeau2013.pdf
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