• Title/Summary/Keyword: Emotion-Structure

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Psychological Structure and ANS Response by Odor Induced Emotion (연령별 향 감성구조 및 향 감성에 따른 자율신경계 반응)

  • 박미경;정희윤;이경화;최정인;이배환;손진훈
    • Science of Emotion and Sensibility
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    • v.4 no.2
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    • pp.39-45
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    • 2001
  • This study was conducted to identify the structure of the sensibility and autonomic nervous responses to odor by ages. 72 participants, 24 each in their teens, twenties, and thirties were given odor stimuli, cederwood, grapefruit, teebaum, peppermint, rose. During the presentation of stimuli, participant were measured blood flow, skin temperature, skin conductance, and ECG and subjective emotion to each odor were evaluated, Five factors, aesthetic, intensity, naturality, uniqueness, and romantism were identified but there were no differences by ages. Emotional factors that predict the preference to certain odors turned out partly different by ages. However, odors that made participants feel sick created more autonomic nervous response than odors that made them feel good.

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A Study on Robust Emotion Classification Structure Between Heterogeneous Speech Databases (이종 음성 DB 환경에 강인한 감성 분류 체계에 대한 연구)

  • Yoon, Won-Jung;Park, Kyu-Sik
    • The Journal of the Acoustical Society of Korea
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    • v.28 no.5
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    • pp.477-482
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    • 2009
  • The emotion recognition system in commercial environments such as call-center undergoes severe system performance degradation and instability due to the speech characteristic differences between the system training database and the input speech of unspecified customers. In order to alleviate these problems, this paper extends traditional method of emotion recognition of neutral/anger into two-step hierarchical structure by using emotional characteristic changes and differences of male and female. The experimental results indicate that the proposed method provides very stable and successful emotional classification performance about 25% over the traditional method of emotion recognition.

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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A Study of the relationship between Fashion Sensibility and Emotion(Part II) (현대패션에 대한 감성과 감정의 관계 연구(제1보))

  • 김유진;이경희
    • Journal of the Korean Society of Clothing and Textiles
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    • v.27 no.3_4
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    • pp.418-428
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    • 2003
  • The purpose of this study was to provide the guidance in more objective and proper clothing design reflecting today's consumers' modes in value consumption by identifying the meaning structure and relationship between fashion sensibility and emotion. The stimulus was 54 photos of contemporary costume which represented the Izard' DES. The questionnaire consisted of hi-polar 25 pairs adjective scale of fashion sensibility and the 18 noun scale of emotion was distributed to 970 male and female living in Pusan area. The data were analyzed by Factor analysis, Correlation analysis and Regression analysis using the statistical SPSS package. The major finding of this research were as follows.1. Fashion sensibilities consist of estheticism, maturity, character and feminity to represent 57.17% total varlarlce. 2. Emotions consist of negative emotion, distress afraid, arousal, shame and enjoyment to represent 70.84% total variance. 3. For the relation between fashion sensibility and emotion, they showed significant relationship in most of factors.

A Study Regarding Head Image′s Through Fashion Collection (패션컬렉션에 나타난 Head Image 연구)

  • 김애경;이경희
    • Journal of the Korean Society of Clothing and Textiles
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    • v.27 no.8
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    • pp.904-912
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    • 2003
  • This study for‘Head Image’, which is affected by individual Image, is via fashion collection to analyze formative feature, fashion emotion and meaning structure of emotion and to inquire into correlation. I will offer fundamental data, which is can use Image making from the state of thing. First, to make charm and personal image, if we consider Head image well, it will very effective by the reason that personality and charm operate as important factors in fashion sensibility of Head Image. Second, we can know Head Image has more strong influence the part of emotion than fashion sensibility by showing that the sense of emotion is higher than this point of view of fashion sensibility in Head Image. Third, As a result of the correlation of fashion sensibility and emotion in Head Image, personal Head Image is effective to attract public gaze by causing negative emotion, and attractive Head Image is effective to give pleasant feeling by causing positive emotion. Forth, Avant-garde, Punk, Kitsch Image were estimated as the most personal things and Romantic, Ethnic Image were estimated as the most attractive things of the type of Head Image. Natural Image was estimated as the most feminine thing, and Elegant Image was estimated as the most mature thing. Fifth, when we look into the different appraisals between experts and amateurs about fashion sensibility and emotion of Head Image, a selection of experts are used to peculiar and strong Head Image, so amateurs respond it more sensitively and highly evaluate.

Causal relationship study of human sense for odor

  • Kaneki, N.;Shimada, K.;Yamada, H.;Miura, T.;Kamimura, H.;Tanaka, H.
    • Proceedings of the Korean Society for Emotion and Sensibility Conference
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    • 2002.05a
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    • pp.257-260
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    • 2002
  • The impressions for odors are subjective and have individual differences. In this study, the Impressions of odors were investigated by covariance structure analysis. 46 subjects (men in their twenty) recorded their reactions to ten odorants by grading them on a seven-point scale in terms of twelve adjective pairs. Their reactions were quantified by using factor analysis and covariance structure analysis. The factors were extracted as "preference", "arousal" and "persistency". The subjects were classified into three groups according to the most suitable causal models (structural equation models). Each group had different causal relationship and different impression structure for odors. It was suggested that there is a possibility to evaluate the subjective impression of odor using covariance structure analysis.

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Classification System of Fashion Emotion for the Standardization of Data (데이터 표준화를 위한 패션 감성 분류 체계)

  • Park, Nanghee;Choi, Yoonmi
    • Journal of the Korean Society of Clothing and Textiles
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    • v.45 no.6
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    • pp.949-964
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    • 2021
  • Accumulation of high-quality data is crucial for AI learning. The goal of using AI in fashion service is to propose of a creative, personalized solution that is close to the know-how of a human operator. These customized solutions require an understanding of fashion products and emotions. Therefore, it is necessary to accumulate data on the attributes of fashion products and fashion emotion. The first step for accumulating fashion data is to standardize the attribute with coherent system. The purpose of this study is to propose a fashion emotional classification system. For this, images of fashion products were collected, and metadata was obtained by allowing consumers to describe their emotions about fashion images freely. An emotional classification system with a hierarchical structure, was then constructed by performing frequency and CONCOR analyses on metadata. A final classification system was proposed by supplementing attribute values with reference to findings from previous studies and SNS data.

A Multimodal Emotion Recognition Using the Facial Image and Speech Signal

  • Go, Hyoun-Joo;Kim, Yong-Tae;Chun, Myung-Geun
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.5 no.1
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    • pp.1-6
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    • 2005
  • In this paper, we propose an emotion recognition method using the facial images and speech signals. Six basic emotions including happiness, sadness, anger, surprise, fear and dislike are investigated. Facia] expression recognition is performed by using the multi-resolution analysis based on the discrete wavelet. Here, we obtain the feature vectors through the ICA(Independent Component Analysis). On the other hand, the emotion recognition from the speech signal method has a structure of performing the recognition algorithm independently for each wavelet subband and the final recognition is obtained from the multi-decision making scheme. After merging the facial and speech emotion recognition results, we obtained better performance than previous ones.

A Study on Emotion Recognition Systems based on the Probabilistic Relational Model Between Facial Expressions and Physiological Responses (생리적 내재반응 및 얼굴표정 간 확률 관계 모델 기반의 감정인식 시스템에 관한 연구)

  • Ko, Kwang-Eun;Sim, Kwee-Bo
    • Journal of Institute of Control, Robotics and Systems
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    • v.19 no.6
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    • pp.513-519
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    • 2013
  • The current vision-based approaches for emotion recognition, such as facial expression analysis, have many technical limitations in real circumstances, and are not suitable for applications that use them solely in practical environments. In this paper, we propose an approach for emotion recognition by combining extrinsic representations and intrinsic activities among the natural responses of humans which are given specific imuli for inducing emotional states. The intrinsic activities can be used to compensate the uncertainty of extrinsic representations of emotional states. This combination is done by using PRMs (Probabilistic Relational Models) which are extent version of bayesian networks and are learned by greedy-search algorithms and expectation-maximization algorithms. Previous research of facial expression-related extrinsic emotion features and physiological signal-based intrinsic emotion features are combined into the attributes of the PRMs in the emotion recognition domain. The maximum likelihood estimation with the given dependency structure and estimated parameter set is used to classify the label of the target emotional states.

Developing an Interactive Character having an Artificial Emotion for a Smart Phone (인공정서를 가진 스마트폰용 인터랙티브 캐릭터 개발)

  • Ham, Jun-Seok;Yeo, Ji-Hye;Park, Sung-Ho;Ko, Il-Ju
    • Science of Emotion and Sensibility
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    • v.14 no.4
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    • pp.483-494
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    • 2011
  • This paper purposes to develop an artificial emotion reflecting emotional features contains situations, time, and characteristics, also to develop an interactive character having this artificial emotion with a smart phone. The artificial emotion has an Emotion Module and Drive Module for expressing emotion according to external emotional stimulus and internal drive. The Emotion Module administrates emotions according to time, characteristic, interrelation between different emotions. The Drive Module controls sensitivities of emotion according to changing drives over long time. Also due to defence mechanism for expressing emotions, emotions are processed by two pathways: The first pathway which is affected by the Emotion Module and the Drive Module, and the second pathway that is not to be done. We developed an interactive character having the artificial emotion with this structure using smart phone. And we simulated the artificial emotion what differences there are according to situations, characteristic, and time under same input conditions. The result of this paper has meanings developing the interactive character having the artificial emotion actually, and making it possible to personalize an artificial emotion with expressing the artificial emotion using smart phone.

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