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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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发表于 2025-3-21 19:22:35 | 显示全部楼层 |阅读模式
期刊全称Affective Information Processing
影响因子2023Jianhua Tao,Tieniu Tan
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发行地址Reports on the state-of-the-art research in affective information processing.Summarises key technologies researched during the last few years, such as affective speech processing. affective facial exp
图书封面Titlebook: Affective Information Processing;  Jianhua Tao,Tieniu Tan Book 2009 Springer-Verlag London 2009 Affect.Affective Computing.Affective Inform
影响因子.Affective information processing assigns computers the human-like capabilities of observation, interpretation and generation of affect features. It is an important topic for harmonious human-computer interaction, by increasing the quality of human-computer communication and improving the intelligence of the computer....Discussing state of art of the research in affective information processing, this book summarises key technologies researched, such as facial expression recognition, face animation, emotional speech synthesis, intelligent agent, and virtual reality. The detailed discussion covers a wide range of topics including hot topics which look to challenge and improve current research work....Written to provide an opportunity for scientists, engineers and graduate students to learn problems, solutions and technologies in the topic area, this book will provide insight and prove a valuable reference tool..
Pindex Book 2009
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发表于 2025-3-21 21:28:36 | 显示全部楼层
Affect and Emotions in Intelligent Agents: Why and How?fit between an organism‘s functioning and the demands and opportunities that are presented by the environment in which it finds itself. It is proposed that effective functioning requires the interplay of four elements—affect, cognition, motivation, and behavior—and that the level of information proc
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Cognitive Emotion Modeling in Natural Language Communicationignificant projects in this domain in recent years. The review is focused on probabilistic dynamic models, due to the key role of uncertainty in the relationships among the variables involved: the authors‘ experience in this domain is discussed by outlining open problems. Two aspects are discussed i
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Affective Agents for Education Against Bullyingstem is discussed and the chapter considers issues relating to believability. It describes the emotionally driven architecture used for characters as well as the management of the overall story and finally considers issues relating to evaluation of systems like this.
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Emotion Perception and Recognition from Speechs more and more important. This chapter begins by introducing the correlations be¬tween basic speech features such as pitch, intensity, formants, MFCC, and so on, and the emotions. Several recognition methods are then described to illustrate the performance of the previously proposed models, includi
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Emotional Speech Generation by Using Statistic Prosody Conversion Methodsression Tree (CART) model. Unlike the rule-based or linear modification method, the GMM and CART models try to map the subtle prosody distributions between neutral and emotional speech. A pitch target model that is optimized to describe Mandarin F0 contours is also introduced. For all conversion met
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Automatic Facial Action Unit Recognition by Modeling Their Semantic And Dynamic Relationshipstion unit (AU) recognition approaches often recognize AUs or certain AU combinations in dividually and statically, ignoring the semantic relationships among AUs and the dynamics of AUs. Hence, these approaches cannot always recognize AUs reliably, robustly, and consistently due to the richness, ambi
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