Kenneth Treharne

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Everyday, millions of people use some form of text-based interface to search inefficiently for information. This reflects a lack of penetration of key developments in Human Computer Interaction (HCI) designed to expedite document retrieval. In the context of document search, the value of textual language is self-evident for searching natural language(More)
Arranging sufficient research participation within time and resource constraints is seldom an easy feat. Often, such constraints are a detriment to thorough empirical evaluation of human-computer interfaces. Our objective is to develop the means to test and construct human models which when applied to interface and system development, result in efficient(More)
Search engine interfaces come in a range of variations from the familiar text-based approach to the more experimental graphical systems. It is rare however that psychological or human factors research is undertaken to properly evaluate or optimize the systems, and to the extent this has been done the results have tended to contradict some of the assumptions(More)
We present a family of Embodied Conversational Agents (ECAs) using Talking Head technology, along with a program of associated research and user trials. Whilst antecedents of our current ECAs include " chatbots " desgined to pass the Turing Test (TT) or win a Loebner Prize (LP), our current agents are task-oriented Teaching Agents and Social Companions. The(More)
Empirical studies assessing the effectiveness of novel document interfaces are becoming more prevalent, however relatively little attention has been paid to how such tools could work with less structured documents featuring multiple contributors. Participants in this study used different interfaces to answer questions requiring the exploration of(More)
Improvements to the user interface of our search tools will play a prominent role toward improving search outcomes in the future. Three such improvements are proposed and evaluated in an exploratory investigation. This is a work in progress and at present, the reported results are preliminary. Nevertheless, significant findings indicate that the way the(More)
—We report on the development of a new simulation environment for use in Multi-Robot Learning, Swarm Robotics, Robot Teaming, Human Factors and Operator Training. The simulator provides a realistic environment for examining methods for localization and navigation, sensor analysis, object identification and tracking, as well as strategy development,(More)
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