How We Talk with Robots: Eliciting Minimally-Constrained Speech to Build Natural Language Interfaces and Capabilities

Abstract

Industry, military, and academia are showing increasing interest in collaborative human-robot teaming in a variety of task contexts. Designing effective user interfaces for human-robot interaction is an ongoing challenge, and a variety of single and multiple-modality interfaces have been explored. Our work is to develop a bi-directional natural language interface for remote human-robot collaboration in physically situated tasks. When combined with a visual interface and audio cueing, we intend for the natural language interface to provide a naturalistic user experience that requires little training. Building the language portion of this interface requires first understanding how potential users would speak to the robot. In this paper, we describe our elicitation of minimally-constrained robot-directed language, observations about the users’ language behavior, and future directions for constructing an automated robotic system that can accommodate these language needs.