1,128 research outputs found

    The dawn of the human-machine era: a forecast of new and emerging language technologies

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    New language technologies are coming, thanks to the huge and competing private investment fuelling rapid progress; we can either understand and foresee their effects, or be taken by surprise and spend our time trying to catch up. This report scketches out some transformative new technologies that are likely to fundamentally change our use of language. Some of these may feel unrealistically futuristic or far-fetched, but a central purpose of this report - and the wider LITHME network - is to illustrate that these are mostly just the logical development and maturation of technologies currently in prototype. But will everyone benefit from all these shiny new gadgets? Throughout this report we emphasise a range of groups who will be disadvantaged and issues of inequality. Important issues of security and privacy will accompany new language technologies. A further caution is to re-emphasise the current limitations of AI. Looking ahead, we see many intriguing opportunities and new capabilities, but a range of other uncertainties and inequalities. New devices will enable new ways to talk, to translate, to remember, and to learn. But advances in technology will reproduce existing inequalities among those who cannot afford these devices, among the world's smaller languages, and especially for sign language. Debates over privacy and security will flare and crackle with every new immersive gadget. We will move together into this curious new world with a mix of excitement and apprehension - reacting, debating, sharing and disagreeing as we always do. Plug in, as the human-machine era dawn

    Resolving Perception Based Problems in Human-Computer Dialogue

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    We investigate the effect of sensor errors on situated human­ computer dialogues. If a human user instructs a robot to perform a task in a spatial environment, errors in the robot\u27s sensor based perception of the environment may result in divergences between the user\u27s and the robot\u27s understanding of the environment. If the user and the robot communicate through a language based interface, these problems may result in complex misunderstand­ ings. In this work we investigate such situations. We set up a simulation based scenario in which a human user instructs a robot to perform a series of manipulation tasks, such as lifting, moving and re-arranging simple objects. We induce errors into the robot\u27s perception, such as misclassification of shapes and colours, and record and analyse the user\u27s attempts to resolve the problems. We evaluate a set of methods to alleviate the problems by allowing the operator to access the robot\u27s understanding of the scene. We investigate a uni-directional language based option, which is based on automatically generated scene descriptions, a visually based option, in which the system highlights objects and provides known properties, and a dialogue based assistance option. In this option the participant can a.sk simple questions about the robot\u27s perception of the scene. As a baseline condition we perform the experiment without introducing any errors. We evaluate and compare the success and problems in all four conditions. We identify and compare strategies the participants used in each condition. We find that the participants appreciate and use the information request options successfully. We find that that all options provide an improvement over the condition without information. We conclude that allowing the participants to access information about the robot\u27s perception state is an effective way to resolve problems in the dialogue

    Multimodal Shared-Control Interaction for Mobile Robots in AAL Environments

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    This dissertation investigates the design, development and implementation of cognitively adequate, safe and robust, spatially-related, multimodal interaction between human operators and mobile robots in Ambient Assisted Living environments both from the theoretical and practical perspectives. By focusing on different aspects of the concept Interaction, the essential contribution of this dissertation is divided into three main research packages; namely, Formal Interaction, Spatial Interaction and Multimodal Interaction in AAL. As the principle package, in Formal Interaction, research effort is dedicated to developing a formal language based interaction modelling and management solution process and a unified dialogue modelling approach. This package aims to enable a robust, flexible, and context-sensitive, yet formally controllable and tractable interaction. This type of interaction can be used to support the interaction management of any complex interactive systems, including the ones covered in the other two research packages. In the second research package, Spatial Interaction, a general qualitative spatial knowledge based multi-level conceptual model is developed and proposed. The goal is to support a spatially-related interaction in human-robot collaborative navigation. With a model-based computational framework, the proposed conceptual model has been implemented and integrated into a practical interactive system which has been evaluated by empirical studies. It has been particularly tested with respect to a set of high-level and model-based conceptual strategies for resolving the frequent spatially-related communication problems in human-robot interaction. Last but not least, in Multimodal Interaction in AAL, attention is drawn to design, development and implementation of multimodal interaction for elderly persons. In this elderly-friendly scenario, ageing-related characteristics are carefully considered for an effective and efficient interaction. Moreover, a standard model based empirical framework for evaluating multimodal interaction is provided. This framework was especially applied to evaluate a minutely developed and systematically improved elderly-friendly multimodal interactive system through a series of empirical studies with groups of elderly persons
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