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A Multimodal Approach to Assessing User Experiences with Agent Helpers / Leigh Clark; Abdulmalik Ofemile; Svenja Adolphs; Tom Rodden
ACM Transactions on Interactive Intelligent Systems, Volume: 6, Issue: 4, Pages: 1 - 31
Swansea University Author: Leigh, Clark
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The study of agent helpers using linguistic strategies such as vague language and politeness has often come across obstacles. One of these is the quality of the agent's voice and its lack of appropriate fit for using these strategies. The first approach of this article compares human vs. synthe...
|Published in:||ACM Transactions on Interactive Intelligent Systems|
Association for Computing Machinery (ACM)
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The study of agent helpers using linguistic strategies such as vague language and politeness has often come across obstacles. One of these is the quality of the agent's voice and its lack of appropriate fit for using these strategies. The first approach of this article compares human vs. synthesised voices in agents using vague language. This approach analyses the 60,000-word text corpus of participant interviews to investigate the differences of user attitudes towards the agents, their voices and their use of vague language. It discovers that while the acceptance of vague language is still met with resistance in agent instructors, using a human voice yields more positive results than the synthesised alternatives. The second approach in this article discusses the development of a novel multimodal corpus of video and text data to create multiple analyses of human-agent interaction in agent-instructed assembly tasks. The second approach analyses user spontaneous facial actions and gestures during their interaction in the tasks. It found that agents are able to elicit these facial actions and gestures and posits that further analysis of this nonverbal feedback may help to create a more adaptive agent. Finally, the approaches used in this article suggest these can contribute to furthering the understanding of what it means to interact with software agents.
The figures in the openly available version of the PDF are skewed. The publisher's version presents a better view of the images.
Human-agent interaction, vague language, instruction giving, gestures, facial actions, emotions
College of Science