Natural language generation for social robotics: opportunities and challenges

Abstract

One contribution of 17 to a theme issue 'From social brains to social robots: applying neurocognitive insights to human -robot interaction'.In the increasingly popular and diverse research area of social robotics, the primary goal is to develop robot agents that exhibit socially intelligent behaviour while interacting in a face-to-face context with human partners. An important aspect of face-to-face social conversation is fluent, flexible linguistic interaction; face-to-face dialogue is both the basic form of human communication and the richest and most flexible, combining unrestricted verbal expression with meaningful non-verbal acts such as gestures and facial displays, along with instantaneous, continuous collaboration between the speaker and the listener. In practice, however, most developers of social robots tend not to use the full possibilities of the unrestricted verbal expression afforded by face-to-face conversation; instead, they generally tend to employ relatively simplistic processes for choosing the words for their robots to say. This contrasts with the work carried out Natural Language Generation (NLG), the field of computational linguistics devoted to the automated production of high-quality linguistic content; while this research area is also an active one, in general most effort in NLG is focused on producing high-quality written text. This article summarizes the state of the art in the two individual research areas of social robotics and natural language generation. It then discusses the reasons why so few current social robots make use of more sophisticated generation techniques. Finally, an approach is proposed to bringing some aspects of NLG into social robotics, concentrating on techniques and tools that are most appropriate to the needs of socially interactive robots.This article is part of the theme issue 'From social brains to social robots: applying neurocognitive insights to human -robot interaction'.

From social brains to social robots: applying neurocognitive insights to human–robot interaction

“…Indeed, social robots need to be able to sense signals from humans, respond adequately, understand and generate natural language, have reasoning capacities, plan actions and execute movements in line with what is required by the specific context or situation. In this part of our theme issue, three contributions cover the areas of research related to technical solutions for HRI: computational architectures [9], classification and prediction of human behaviour and expressions [10], and natural language processing [11]. These three contributions provide examples of challenges that roboticists and artificial intelligence experts need to face in order to design robots endowed with capabilities crucial for social interactions with humans.…”

“…Finally, Foster [11] addresses another crucial competence that is required to enable natural HRI: the ability of the technical system to understand spoken natural language and respond appropriately. Foster provides an overview of methods used in HRI for natural language generation.…”

Development Issues of Healthcare Robots: Compassionate Communication for Older Adults with Dementia

“…HCRs are envisioned to deliver meaningful benefits through effective interaction with humans to fulfil their expectations [ 41 ]. In contrast to automation, which follows pre-programmed “rules” and is limited to specific actions, autonomous robots are required to have a context-guided behavior adaptation capability, which would allow them to have a degree of self-governance [ 42 ]. It should enable them to learn and respond actively to situations that were not pre-programmed by the developer.…”

Engineering Reliable Interactions in the Reality-Artificiality Continuum

“…However, to be believable and pleasant companions, robots should also generate natural language. The reasons why so few current social robots make use of sophisticated generation techniques are discussed by Foster in her paper on "natural language generation for social robotics: opportunities and challenges" [22].…”