The HCI community is actively seeking novel methodologies to gain insight into the user's experience during interaction with both the application and the content. We propose an emotional recognition engine capable of automatically recognizing a set of human emotional states using psychophysiological measures of the autonomous nervous system, including galvanic skin response, respiration, and heart rate. A novel pattern recognition system, based on discriminant analysis and support vector machine classifiers is trained using movies' scenes selected to induce emotions ranging from the positive to the negative valence dimension, including happiness, anger, disgust, sadness, and fear. In this paper we introduce an emotion recognition system and evaluate its accuracy by presenting the results of an experiment conducted with three physiologic sensors.
Information awareness is the process by which people obtain knowledge about the status of personal information that is important to them. This is usually provided graphically. When the information would otherwise be hidden from view, it must be brought to the front automatically or manually making users stop what they are doing and interact with the system. This design strategy ignores the human costs of interrupting the user. A solution is to use speech output to make the delivery invisible, but the incorporation of speech invokes anthropomorphic feelings whose cues must be carefully controlled if the system is to be regarded as humanised. This paper describes an empirical study designed to investigate how the content contextually cues the significance of visually hidden information, and how the delivery, including attentive interruptions, linguistic variation and politeness, impacts on the social acceptability of a speaking system. The results indicated that heuristic-oriented people felt a degree of rapport with the speech-based system, and that it enabled them to appreciate the content of hidden information more strongly than those who were analytic 2 Nuno M Ribeiro & Ian D Benest in nature. Overall, the system was unexpectedly well accepted, leading to the abstraction of design guidelines for those speech-based systems that exploit invisibility to enhance information awareness.
Video growth over the Internet changed the way users search, browse and view video content. Watching movies over the Internet is increasing and becoming a pastime. The possibility of streaming Internet content to TV, advances in video compression techniques and video streaming have turned this recent modality of watching movies easy and doable. Web portals as a worldwide mean of multimedia data access need to have their contents properly classified in order to meet users’ needs and expectations. The authors propose a set of semantic descriptors based on both user physiological signals, captured while watching videos, and on video low-level features extraction. These XML based descriptors contribute to the creation of automatic affective meta-information that will not only enhance a web-based video recommendation system based in emotional information, but also enhance search and retrieval of videos affective content from both users’ personal classifications and content classifications in the context of a web portal.
Emotional information is being used in several systems as a way to understand users while interacting with computers or as a way to explore content classification. Movies are a medium emotionally empowered and technological developments and trends for media convergence are turning video into a dominant and pervasive medium, and online video is becoming a growing entertainment activity on the web. In this paper we present a user interface for movies' emotion exploration based on a previous usability study. Felt-is an application for movie and users' emotions exploration as a way to access movies by its emotional properties or as a way of recommending movies by the analysis of users emotional profiles. In this paper we also propose novel interactive mechanisms for movie's emotions exploration.
Organizações que aprendem relacionam resultados ao crescimento pessoal de seus colaboradores. Assim, muitas são as possibilidades de busca por desenvolvimento por parte das organizações e autodesenvolvimento por parte dos colaboradores. Com esse objetivo foi realizado um estudo comparativo entre trilhas de aprendizagem e metodologias ativas. Para realizar a comparação foram entrevistadas às Universidade Corporativa do Banco do Brasil, a Universidade Corporativa do Sebrae, a Escola de Contas do Distrito Federal e a Escola Nacional de Administração Pública que ofertam capacitação no formato de trilhas de aprendizagem. Os resultados foram comparados às 5 técnicas de metodologias ativas que apontaram como resultado que as duas abordagens são voltadas para quantidade diferentes de colaboradores a desenvolver competências. Além das trilhas de aprendizagem e as metodologias ativas, o conceito de metodologias ágeis emergiu como indicado para o autodesenvolvimento e a capacitação de gestores. Assim, as metodologias ágeis também foram objeto de comparação no estudo.
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