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Titlebook: Affective Information Processing; Jianhua Tao,Tieniu Tan Book 2009 Springer-Verlag London 2009 Affect.Affective Computing.Affective Inform

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樓主: 爆裂
21#
發(fā)表于 2025-3-25 05:59:18 | 只看該作者
A Linguistic Interpretation of the OCC Emotion Model for Affect Sensing from Textecific values of the cognitive variables of the emotion model. The resulting linguistics-based rule set for the OCC emotion types and cognitive states allows us to determine a broad class of emotions conveyed by text.
22#
發(fā)表于 2025-3-25 08:11:53 | 只看該作者
23#
發(fā)表于 2025-3-25 12:10:00 | 只看該作者
24#
發(fā)表于 2025-3-25 15:52:16 | 只看該作者
25#
發(fā)表于 2025-3-25 23:03:48 | 只看該作者
Physiological Sensing for Affective Computingapplications rely on today, and commonly used techniques to access them. After this, requirements of affective applications for physiological sensors are worked out. A design concept meeting the requirements is drawn and exemplary implementations including evaluation results are described.
26#
發(fā)表于 2025-3-26 02:39:34 | 只看該作者
27#
發(fā)表于 2025-3-26 05:48:06 | 只看該作者
https://doi.org/10.1007/978-3-319-63480-7elationships among the variables involved: the authors‘ experience in this domain is discussed by outlining open problems. Two aspects are discussed in particular: how probabilistic emotion models can be validated and how the problem of emotional-cognitive inconsistency can be dealt with in probabilistic terms.
28#
發(fā)表于 2025-3-26 09:55:03 | 只看該作者
29#
發(fā)表于 2025-3-26 16:31:41 | 只看該作者
Expressive Speech Synthesis: Past, Present, and Possible Futureslicit control” paradigm in statistical parametric speech synthesis, which provides control over expressivity by combining and interpolating between statistical models trained on different expressive databases. The present chapter provides an overview of the past and present approaches, and ventures a look into possible future developments.
30#
發(fā)表于 2025-3-26 18:14:57 | 只看該作者
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