摘要：The goal of SecondHands, a H2020 project, is to design a robot that can offer help to a maintenance technician in a proactive manner. The robot is to act as a second pair of hands that can assist the technician when he is in need of help. In order for the robot to be of real help to the technician, it needs to understand his needs and follow his commands. Interaction via speech is a crucial part of this. Due to the nature of the situation in which the interactions take place, often the technician needs to speak to the robot when under stress performing strenuous physical labor, the classical turn based interaction schemes need to be transformed into dialogue systems that perform stream processing, anticipating user intentions, correcting itself as more information become available, in order to be able to respond in a rapid manner. In order to meet these demands, we are developing low-latency streaming based automatic speech recognition systems in combination with recurrent neural network based Natural Language Understanding systems that perform slot filling and intent recognition in order for the robot to provide assistance in a rapid manner, that can be partly based on speculative classifications that are then being refined as more speech becomes available.
