Views from within a narrative : Evaluating long-term human-robot interaction in a naturalistic environment using open-ended scenarios

Open Access This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited. Date of acceptance: 16/06/2014This article describes the prototyping of human–robot interactions in the University of Hertfordshire (UH) Robot House. Twelve participants took part in a long-term study in which they interacted with robots in the UH Robot House once a week for a period of 10 weeks. A prototyping method using the narrative framing technique allowed participants to engage with the robots in episodic interactions that were framed using narrative to convey the impression of a continuous long-term interaction. The goal was to examine how participants responded to the scenarios and the robots as well as specific robot behaviours, such as agent migration and expressive behaviours. Evaluation of the robots and the scenarios were elicited using several measures, including the standardised System Usability Scale, an ad hoc Scenario Acceptance Scale, as well as single-item Likert scales, open-ended questionnaire items and a debriefing interview. Results suggest that participants felt that the use of this prototyping technique allowed them insight into the use of the robot, and that they accepted the use of the robot within the scenarioPeer reviewe

Towards an Emotionally Intelligent Interaction Strategy for Multimodal Embodied Conversational Agents acting as Companions

Existing Human Computer Interaction (HCI) strategies are seriously limited by current technologies. These are neither sensitive nor accurate enough to respond to users’ emotional states, the fundamental basis for effective communication in real time. This offered the challenge of investigating factors that would impact on the designing of effective and more emotionally intelligent interaction strategies for Companions. These were applied to a conceptual tool, the Affective Channel (AC), to endow Companions with emotional capabilities. This was implemented in the Wizard of Oz (WoZ) platform to evaluate Companions in real time. The WoZ is an experimental setup where existing immature technologies and a human operator combine to simulate Companion interaction with end users. In these aspects of my work is my original contribution to the HCI knowledge base.Experiments, focus groups and face to face interviews were carried out to ascertain users’ perception and expectations of virtual agents. ‘Descriptors’ thus identified formed the bases for the designing of user friendly Companions. Verbal and facial expressions data and other affective elements of effective human-companion interactionwere collected for use in the AC and the WoZ as stated above.Companion evaluations yielded the subsidiary contribution that Companions are perceived as empathetic, useful and trustworthy entities. Further, that they arouse positive emotions in children and also that they promote their learning improvement.These findings were the result of two experiments, one within subjects and one between subjects, conducted with thirty grade four pupils in a rural school in the poor Oaxaca region of Mexico

Robust Dialog Management Through A Context-centric Architecture

This dissertation presents and evaluates a method of managing spoken dialog interactions with a robust attention to fulfilling the human user’s goals in the presence of speech recognition limitations. Assistive speech-based embodied conversation agents are computer-based entities that interact with humans to help accomplish a certain task or communicate information via spoken input and output. A challenging aspect of this task involves open dialog, where the user is free to converse in an unstructured manner. With this style of input, the machine’s ability to communicate may be hindered by poor reception of utterances, caused by a user’s inadequate command of a language and/or faults in the speech recognition facilities. Since a speech-based input is emphasized, this endeavor involves the fundamental issues associated with natural language processing, automatic speech recognition and dialog system design. Driven by ContextBased Reasoning, the presented dialog manager features a discourse model that implements mixed-initiative conversation with a focus on the user’s assistive needs. The discourse behavior must maintain a sense of generality, where the assistive nature of the system remains constant regardless of its knowledge corpus. The dialog manager was encapsulated into a speech-based embodied conversation agent platform for prototyping and testing purposes. A battery of user trials was performed on this agent to evaluate its performance as a robust, domain-independent, speech-based interaction entity capable of satisfying the needs of its users