828 resultados para Emotion annotation-scheme
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We present a machine learning-based system for automatically computing interpretable, quantitative measures of animal behavior. Through our interactive system, users encode their intuition about behavior by annotating a small set of video frames. These manual labels are converted into classifiers that can automatically annotate behaviors in screen-scale data sets. Our general-purpose system can create a variety of accurate individual and social behavior classifiers for different organisms, including mice and adult and larval Drosophila.
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Recent empirical work on the semantics of emotion terms across many different cultures and languages, using a theoretical componential approach, suggested that four dimensions are needed to parsimoniously describe the semantic space of the emotion domain as reflected in emotion terms (Fontaine, Scherer, Roesch, & Ellsworth, 2007; Fontaine, Scherer, & Soriano, 2013). In addition to valence, power, and arousal, a novelty dimension was discovered that mostly differentiated surprise from other emotions. Here, we further explore the existence and nature of the fourth dimension in semantic emotion space using a much larger and much more representative set of emotion terms. A group of 156 participants each rated 10 out of a set of 80 French emotion terms with respect to semantic meaning. The meaning of an emotion term was evaluated with respect to 68 emotion features representing the appraisal, action tendency, bodily reaction, expression, and feeling components of the emotion process. A principal component analysis confirmed the four-dimensional valence, power, arousal, and novelty structure. Moreover, this larger and much more representative set of emotion terms revealed that the novelty dimension not only differentiates surprise terms from other emotion terms, but also identifies substantial variation within the fear and joy emotion families.
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Research on emotion inferences has shown that readers include a representation of the main character's emotional state in their mental representations of the text. We examined the specificity of emotion representations as a function of the emotion content of short narratives, in terms of the quantity and quality of emotion components included in the narratives, based on the GRID instrument (Fontaine et al., 2013). In a self-paced reading task, target sentences that only moderately matched the emotional context were read faster than target sentences that strongly matched the emotional context of the narratives. In a “makes sense” judgment task, we showed that this result was not driven by a mapping difficulty and, in a memory task, we provided some evidence that these effects reflected integration processes. We suggest that readers can integrate specific emotions into their mental representations, but only if provided with the appropriate emotional contextual support.
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Includes index.
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At head of title: "In-house Laboratory Independent Research Program."
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Mode of access: Internet.
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National Highway Traffic Safety Administration, Washington, D.C.
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National Highway Traffic Safety Administration, Washington, D.C.
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Includes index.
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COO 1469-0194.
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Bibliography: p. 36.
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Document originally completed in April 1967.