• Title/Summary/Keyword: Emotion System

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Emotional Model for an Android based on Hormone Model (호르몬 모델에 기반한 안드로이드의 감정모델)

  • Lee, Dong-Wook;Lee, Tae-Geun;Jung, Jun-Young;So, Byung-Rok;Shon, Woong-Hee;Baeg, Moon-Hon;Kim, Hong-Seok;Lee, Ho-Gil
    • The Journal of Korea Robotics Society
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    • v.2 no.4
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    • pp.341-345
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    • 2007
  • This paper proposes an emotional interaction model between human and robot using an android. An android is a sort of humanoid robot that the outward shape of robot is almost the same as that of human. The android is a robot platform to implement and test emotional expressions and human interaction. In order to behave for the android like human, a structure of internal emotion system is very important. In our research, we propose a novel emotional model of android based on biological hormone and emotion space. Proposed emotion model has an advantage that it can represent emotion change as time by hormone dynamics.

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The Analysis of Emotion Adjective for LED Light Colors by using Kobayashi scale and I.R.I scale (Kobayashi 스케일과 I.R.I 스케일을 사용한 LED 광색의 형용사 이미지 분석)

  • Baek, Chang-Hwan;Park, Seung-Ok;Kim, Hong-Suk
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.25 no.10
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    • pp.1-13
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    • 2011
  • The aim of this study is to analyze the emotion adjectives for light emitting diode(LED) light colors using a twofold adjective image scales from Kobayashi and I.R.I. A set of psychophysical experiments using category judgment was conducted in an LED light color simulation system, in order to evaluate each emotion scale coordinate for those test light colors in both adjective image scales. In total, 49 test light colors from a combination of 6 color series were assessed by 15 human observers. As a result, Kobayashi adjective image scale clearly expressed to emotion adjectives of 'Dynamic', 'Casual', 'Chic', 'Cool-casual', 'Modern', and 'Natural' for different hues. In contrast, I.R.I adjective image scale expressed only 2 adjectives of 'dynamic' and 'luxurious' for the all hues.

The Pattern Recognition Methods for Emotion Recognition with Speech Signal (음성신호를 이용한 감성인식에서의 패턴인식 방법)

  • Park Chang-Hyeon;Sim Gwi-Bo
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2006.05a
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    • pp.347-350
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    • 2006
  • In this paper, we apply several pattern recognition algorithms to emotion recognition system with speech signal and compare the results. Firstly, we need emotional speech databases. Also, speech features for emotion recognition is determined on the database analysis step. Secondly, recognition algorithms are applied to these speech features. The algorithms we try are artificial neural network, Bayesian learning, Principal Component Analysis, LBG algorithm. Thereafter, the performance gap of these methods is presented on the experiment result section. Truly, emotion recognition technique is not mature. That is, the emotion feature selection, relevant classification method selection, all these problems are disputable. So, we wish this paper to be a reference for the disputes.

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Reinforcement Learning Method Based Interactive Feature Selection(IFS) Method for Emotion Recognition (감성 인식을 위한 강화학습 기반 상호작용에 의한 특징선택 방법 개발)

  • Park Chang-Hyun;Sim Kwee-Bo
    • Journal of Institute of Control, Robotics and Systems
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    • v.12 no.7
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    • pp.666-670
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    • 2006
  • This paper presents the novel feature selection method for Emotion Recognition, which may include a lot of original features. Specially, the emotion recognition in this paper treated speech signal with emotion. The feature selection has some benefits on the pattern recognition performance and 'the curse of dimension'. Thus, We implemented a simulator called 'IFS' and those result was applied to a emotion recognition system(ERS), which was also implemented for this research. Our novel feature selection method was basically affected by Reinforcement Learning and since it needs responses from human user, it is called 'Interactive feature Selection'. From performing the IFS, we could get 3 best features and applied to ERS. Comparing those results with randomly selected feature set, The 3 best features were better than the randomly selected feature set.

Emotion Recognition of Facial Expression using the Hybrid Feature Extraction (혼합형 특징점 추출을 이용한 얼굴 표정의 감성 인식)

  • Byun, Kwang-Sub;Park, Chang-Hyun;Sim, Kwee-Bo
    • Proceedings of the KIEE Conference
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    • 2004.05a
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    • pp.132-134
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    • 2004
  • Emotion recognition between human and human is done compositely using various features that are face, voice, gesture and etc. Among them, it is a face that emotion expression is revealed the most definitely. Human expresses and recognizes a emotion using complex and various features of the face. This paper proposes hybrid feature extraction for emotions recognition from facial expression. Hybrid feature extraction imitates emotion recognition system of human by combination of geometrical feature based extraction and color distributed histogram. That is, it can robustly perform emotion recognition by extracting many features of facial expression.

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A Fundamental Study on the Marine Leisure - focus on the Psychology of Emotion for Seashore Relaxation - (해양레저에 관한 기초적인 연구 - 해변휴양의 정서심리를 중심으로 -)

  • Yoon, Soon-Dong
    • Proceedings of KOSOMES biannual meeting
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    • 2008.05a
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    • pp.75-80
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    • 2008
  • There are a lot of interest and research on practical area of marine leisure but few research on fundamental area. We need to suggest the theoretical basis on the merit of marine leisure. The author analyzed in visual and audio informations of seashore environment based on psychology of emotion aesthetically and musically. As a results, Peoples could get affirmative emotion through participating in seashore relaxation and changed their negative emotion into affirmative.

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