Context-aware Spoken Language Understanding for Human Robot Interaction

Robots operate in specific environments and the correct interpretation of linguistic interactions depends on physical, cognitive and language-dependent aspects triggered by the environment. In this work, we present LU4R - adaptive spoken Language Understanding 4 Robots, a Spoken Language Understanding chain for the semantic interpretation of robotic commands, that is sensitive to the operational environment. The system has been designed according to a Client/Server architecture in order to be easily integrated with the vast plethora of robotic platforms.