Whither the Priors for (Vocal) Interactivity?

Abstract

Voice-based communication is often cited as one of the most 'natural' ways in which humans and robots might interact, and the recent availability of accurate automatic speech recognition and intelligible speech synthesis has enabled researchers to integrate advanced off-the-shelf spoken language technology components into their robot platforms. Despite this, the resulting interactions are anything but 'natural'. It transpires that simply giving a robot a voice doesn't mean that a user will know how (or when) to talk to it, and the resulting 'conversations' tend to be stilted, one-sided and short. On the surface, these difficulties might appear to be fairly trivial consequences of users' unfamiliarity with robots (and vice versa), and that any problems would be mitigated by long-term use by the human, coupled with 'deep learning' by the robot. However, it is argued here that such communication failures are indicative of a deeper malaise: a fundamental lack of basic principlespriorsunderpinning not only speech-based interaction in particular, but (vocal) interactivity in general. This is evidenced not only by the fact that contemporary spoken language systems already require training data sets that are orders-of-magnitude greater than that experienced by a young child, but also by the lack of design principles for creating effective communicative humanrobot interaction. This short position paper identifies some of the key areas where theoretical insights might help overcome these shortfalls.

Working with troubles and failures in conversation between humans and robots: workshop report

“…And, if yes, what does that mean for potential error management in HRI? If priors shared between interlocutors matter (Huang and Moore, 2022;Moore, 2022), how does the aligning of interactive affordances help to increase the system's capacity to deal with errors? Moreover, errors can affect people's perception of a robot's trustworthiness and reliability (e.g., Washburn et al, 2020b), as well as their acceptance and willingness to cooperate in HRI (e.g., Salem et al, 2015).…”