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2016 13th Conference on Computer and Robot Vision (CRV) (2016)
Victoria, BC, Canada
June 1, 2016 to June 3, 2016
ISBN: 978-1-5090-2492-6
pp: 376-382
This paper presents a learning-based frameworknamed SmartTalk for natural-language human-robot interaction (HRI). The primary goal of this framework is to enable non-expert users to control and program a mobile robot using natural language commands. SmartTalk is modality-agnostic, and is capable of integrating with both speech and non-speech (e.g., gesture-based) communication. Initially, robots using this mechanism are equipped with a limited vocabulary of primitive commands and functionality, however, through extended use andinteraction, the robots are able to learn new commands and adapt to user's behaviors and habits. This makes the proposed framework highly desirable for long-term deployment in a variety of HRI tasks. We present the design of this framework and experimental data on a number of realistic scenarios to evaluate its performance. A qualitative experiment on a robotic platform is also presented.
Natural languages, Speech recognition, Mobile robots, Robot sensing systems, Speech, Uncertainty

C. Fabbri and J. Sattar, "SmartTalk: A Learning-Based Framework for Natural Human-Robot Interaction," 2016 13th Conference on Computer and Robot Vision (CRV), Victoria, BC, Canada, 2016, pp. 376-382.
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