LU4R: adaptive spoken language understanding for robots

Service robots are expected to operate in specific environments, where the presence of humansplays a key role. It is thus essential to enable for a natural and effective communication amonghumans and robots. One of the main features of such robotics platforms is the ability to react tospoken commands. This requires a comprehensive understanding of the user utterance to triggerthe robot reaction. Moreover, the correct interpretation of linguistic interactions depends onphysical, cognitive and language-dependent aspects related to the environment. In this work, wepresent the latest version of LU4R - adaptive spoken Language Understanding 4 Robots, a Spo-ken Language Understanding framework for the semantic interpretation of robotic commands,that is sensitive to the operational environment. The overall system is designed according to aClient/Server architecture in order to be easily deployed in a vast plethora of robotic platforms.Moreover, an improved version of HuRIC - Human-Robot Interaction Corpus is presented. Themain novelty presented in this paper is the extension to commands expressed in Italian. In orderto prove the effectiveness of such system, we also present some empirical results in both Englishand Italian computed over the new HuRIC resource.