Assessing User Expertise in Spoken Dialog System Interactions

Identifying the level of expertise of its users is important for a system since it can lead to a better interaction through adaptation techniques. Furthermore, this information can be used in offline processes of root cause analysis. However, not much effort has been put into automatically identifying the level of expertise of an user, especially in dialog-based interactions. In this paper we present an approach based on a specific set of task related features. Based on the distribution of the features among the two classes - Novice and Expert - we used Random Forests as a classification approach. Furthermore, we used a Support Vector Machine classifier, in order to perform a result comparison. By applying these approaches on data from a real system, Let's Go, we obtained preliminary results that we consider positive, given the difficulty of the task and the lack of competing approaches for comparison.Comment: 10 page

Managing technological transitions: prospects, places, publics and policy

Transition management (TM) approaches have generated considerable interest in academic and policy circles in recent years (Kemp and Loorbach, 2005; Rotmans and Kemp, 2003). In terms of a loose definition, a ‘transition can be defined as a gradual, continuous process of structural change within a society or culture’ (Rotmans et al, 2001, p.2). The development of TM, much of which has occurred within the context of the Netherlands, may be seen as a response to the complexities, uncertainties and problems which confront many western societies, in organising ‘sustainably’ various aspects of energy, agricultural, water, transport and health systems of production and consumption. Problems such as pollution, congestion, the vulnerability of energy or water supplies and so on are seen as systemic and entwined or embedded in a series of social, economic, political, cultural and technological relationships. The systemic nature of many of these problems highlights the involvement - in the functioning of a particular system and any subsequent transition - of multiple actors or ‘stakeholders’ across different local, national and international scales of activity. With this in mind, such problems become difficult to ‘solve’ and ‘solutions’ are seen to require systemic innovation rather than individual or episodic responses. The point being that ‘these problems are system inherent and… the solution lies in creating different systems or transforming existing ones’ (Kemp and Loorbach, 2005, p.125). In this paper we critically engage with and build upon transitions approaches to address their ‘applicability’ in the context of the UK. In doing this the paper addresses the prospective potential of transitions approaches, but also their relative neglect of places and publics. Through developing an argument which addresses the strengths and ‘gaps’ of transitions approaches we also analyse the resonances and dissonances between three themes – cities and regions, public participation and national hydrogen strategy – in the transitions literature and the UK policy context

Adaptive User-Centered Multimodal Interaction towards Reliable and Trusted Automotive Interfaces

With the recently increasing capabilities of modern vehicles, novel approaches for interaction emerged that go beyond traditional touch-based and voice command approaches. Therefore, hand gestures, head pose, eye gaze, and speech have been extensively investigated in automotive applications for object selection and referencing. Despite these significant advances, existing approaches mostly employ a one-model-fits-all approach unsuitable for varying user behavior and individual differences. Moreover, current referencing approaches either consider these modalities separately or focus on a stationary situation, whereas the situation in a moving vehicle is highly dynamic and subject to safety-critical constraints. In this paper, I propose a research plan for a user-centered adaptive multimodal fusion approach for referencing external objects from a moving vehicle. The proposed plan aims to provide an open-source framework for user-centered adaptation and personalization using user observations and heuristics, multimodal fusion, clustering, transfer-of-learning for model adaptation, and continuous learning, moving towards trusted human-centered artificial intelligence

Combining heterogeneous inputs for the development of adaptive and multimodal interaction systems

In this paper we present a novel framework for the integration of visual sensor networks and speech-based interfaces. Our proposal follows the standard reference architecture in fusion systems (JDL), and combines different techniques related to Artificial Intelligence, Natural Language Processing and User Modeling to provide an enhanced interaction with their users. Firstly, the framework integrates a Cooperative Surveillance Multi-Agent System (CS-MAS), which includes several types of autonomous agents working in a coalition to track and make inferences on the positions of the targets. Secondly, enhanced conversational agents facilitate human-computer interaction by means of speech interaction. Thirdly, a statistical methodology allows modeling the user conversational behavior, which is learned from an initial corpus and improved with the knowledge acquired from the successive interactions. A technique is proposed to facilitate the multimodal fusion of these information sources and consider the result for the decision of the next system action.This work was supported in part by Projects MEyC TEC2012-37832-C02-01, CICYT TEC2011-28626-C02-02, CAM CONTEXTS S2009/TIC-1485Publicad

Investigating Innovative Models of Governance and Collaboration for Effective Public Administration in a Multi-Stakeholder Landscape

This thesis investigates innovative models of governance and collaboration in public administration to address the complexities of a multi-stakeholder landscape. The study explores the principles, characteristics, types, benefits, and challenges of collaborative governance, public-private partnerships, networked governance, and cross-sectoral collaboration. The research utilizes qualitative and quantitative methods, including interviews, surveys, and document analysis, to gather comprehensive insights. The findings showcase the importance of embracing new approaches that involve government agencies, private sector organizations, and civil society groups working together to tackle complex societal challenges. Tables present the key elements of each model, providing a visual comparison of their features and real-world applications. Additionally, the study highlights evaluation frameworks, such as the Logic Model, Results-Based Management (RBM), Theory of Change, Impact Evaluation, and Utilization-Focused Evaluation, to assess effectiveness and measure impact. The thesis contributes to the field of public administration by emphasizing the significance of collaborative governance and cross-sectoral collaboration. The research provides insights for policymakers, public administrators, and practitioners to adopt effective approaches in addressing challenges and achieving desired outcomes. By embracing innovative models of governance and collaboration, public administration can foster cooperation, inclusivity, and collective problem-solving among stakeholders. The study concludes with a call for further research and implementation of these approaches to create a resilient, responsive, and sustainable public administration system that delivers meaningful impact to society

A hydrogen framework for the East Midlands

Profiles capabilities in midlands-based organisations in hydrogen and fuel cell technologies as a rationale for support of a Midlands hydrogen cluster

On the Development of Adaptive and User-Centred Interactive Multimodal Interfaces

Multimodal systems have attained increased attention in recent years, which has made possible important improvements in the technologies for recognition, processing, and generation of multimodal information. However, there are still many issues related to multimodality which are not clear, for example, the principles that make it possible to resemble human-human multimodal communication. This chapter focuses on some of the most important challenges that researchers have recently envisioned for future multimodal interfaces. It also describes current efforts to develop intelligent, adaptive, proactive, portable and affective multimodal interfaces

Policies for capacity development

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