Exploring vague language use and voice variation in human-agent interaction - Clark, Leigh M.H. (2016)
This thesis addresses the linguistic phenomenon of vague language (VL) and its effect on the creation of identity in the emerging and developing field of human-agent interaction (HAI). Current research on VL has focused on human interaction, while similar existing literature on language in HAI has focused on politeness theory and facework. This thesis brings the two research fields together and uses them as a focusing lens to investigate the issue of identity in agents – software with varying degrees of autonomy and intelligence. Agents are increasingly common in our everyday lives, particularly in the role of an instructor. Intelligent personal assistants are a frequent feature on smartphones, automated checkout systems pervade supermarkets both large and small, and satellite navigation systems have been a mainstay for over a decade now. Despite their frequency, there is relatively little research into the communication challenges surrounding HAI. Much like other people, the language and voice of agents have the ability to affect our perceptions and of them, and shape the way in which we create their identities. Instruction giving, amongst other facets of talk, in human communication can be mitigated through the use of VL. This can reduce the imposition we have on interaction partners, pay respect to a listener’s face, and establish and maintain a positive rapport with our interlocutors. This can have a profound effect on the desire to interact with someone again. Furthermore, agents that use speech to communicate are assigned one of two varieties of voice – synthesised or pre-recorded human speech, both of which have documented benefits and drawbacks. Given the rise of agents in the modern world, it is in the best interest of all parties to understand the salient variables that affect our perceptions of agents, and what effect VL and other variables such as voice in language and voice may have in our interactions with them. This thesis provides a novel approach to investigating both VL and voice in HAI. A general framework is presented with the use of a specific VL model to apply in the interactions, which is designed around verbal agents giving people instructions on how to construct Lego models. The first study compares the effects of a vague and non-vague verbal agent in this context, while the second study focuses on the comparative use of synthesised text-to-speech voices and professional human recordings in the same context. The results from the investigation reveal key findings regarding the use of VL in a verbal agent instructive context. The first study indicated that a synthesised agent voice is better suited to using non-vague instructions, while the second study revealed that a professional voice actor is a preferable candidate for using VL in comparison to two different synthesised voices. These findings discuss the issue of identities in HAI. They reveal that, when an agent instructor is perceived to have a voice that is non-human and machinelike, it is more likely that its use of VL will be received less positively. This is often because the combination of voice and language do not mix, but is also a result of a clash of perceived group identities between agent and human speech. As agents are typically direct, the use of “humanlike” VL can create a large disparity between a person’s expectations of agent speech and the reality of the interaction. Similarly, if an agent’s voice has more of a humanlike feel to it, then its use of VL will create less disparity and has the potential to bridge the gap between these two group identities. This poses discussions on the nature of agent identity and how it compares to those in humans. The thesis concludes with reflection on the findings in light of existing linguistic theories, and how further research into this field may assist agent designers, researchers, and agent users alike. A suggestion of employing a corpus linguistics approach to HAI is proposed, which may pave the way for future success in this area.