• Journal of IKEEE
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• v.24 no.4
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• pp.998-1003
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• 2020

In this paper, an emotion training method using emotional adaptation is proposed to improve the performance of the existing emotion recognition system. For emotion adaptation, an emotion speech model was created from a speech model without emotion using a small number of training emotion voices and emotion adaptation methods. This method showed superior performance even when using a smaller number of emotional voices than the existing method. Since it is not easy to obtain enough emotional voices for training, it is very practical to use a small number of emotional voices in real situations. In the experimental results using a Korean database containing four emotions, the proposed method using emotional adaptation showed better performance than the existing method.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.05a
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• pp.199-202
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• 2001

We, Human beings, use both powers of reason and emotion simultaneously, which surely help us to obtain flexible adaptability against the dynamic environment. We assert that this principle can be applied into the general system. That is, it would be possible to improve the adaptability by covering a digital oriented information processing system with an analog oriented emotion layer. In this paper, we proposed a vertical slicing model with an emotion layer in it. And we showed that the emotion-based control allows us to improve the adaptability of a system at least under some conditions.

• Proceedings of the KIEE Conference
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• 2008.04a
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• pp.99-100
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• 2008

This paper proposes a Gaussian Mixture Model (GMM) - based speech emotion recognition methods using four feature parameters; 1) Fast Fourier Transform(FFT) spectral entropy, 2) delta FFT spectral entropy, 3) Mel-frequency Filter Bank (MFB) spectral entropy, and 4) delta MFB spectral entropy. In addition, we use four emotions in a speech database including anger, sadness, happiness, and neutrality. We perform speech emotion recognition experiments using each pre-defined emotion and gender. The experimental results show that the proposed emotion recognition using FFT spectral-based entropy and MFB spectral-based entropy performs better than existing emotion recognition based on GMM using energy, Zero Crossing Rate (ZCR), Linear Prediction Coefficient (LPC), and pitch parameters. In experimental Results, we attained a maximum recognition rate of 75.1% when we used MFB spectral entropy and delta MFB spectral entropy.

• Proceedings of the IEEK Conference
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• 2001.06e
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• pp.227-230
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• 2001

We, Human beings, use both powers of reason and emotion simultaneously, which surely help us to obtain flexible adaptability against the dynamic environment. We assert that this principle can be applied into the general system. That is, it would be possible to improve the adaptability by covering a digital oriented information processing system with an analog oriented emotion layer. In this paper. we proposed a vertical slicing model with an emotion layer in it. And we showed that the emotion-based control allows us to improve the adaptability of a system at least under some conditions.

• Journal of Korea Game Society
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• v.14 no.2
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• pp.7-18
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• 2014

Emotion is one of the elements of the game that will help the user interaction. The way to express the emotions and personality of the character was taken into account severity of reaction to action or a specific graphics in the game so far. However recently structured for the interest in the study of emotion increases and to utilize a variety of feelings in the game is needed. In the field of autonomous agents, studies of the possibility of the use of emotion, defined 12 different emotion rules. In this paper, we dilate by defining the terms used in the game rules of emotion made the rules of the emotion of the game. And, we analyzed emotions in actual game character used Game Emotions Rule. As a result, it was possible to see the rules of the game feeling separate from that being used for game genre similar.

• Asian Journal of Business Environment
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• v.5 no.4
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• pp.13-18
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• 2015

Purpose - Based on previous studies, this study extends current research and investigates whether the sub-factors of emotional intelligence increase job satisfaction or employee intrinsic and extrinsic motivation and perceived organizational support. Research design, data, and methodology - This study categorizes service employees' (consultants) emotional intelligence into four sub-factors: regulation of emotion, appraisal of emotion, utilization of emotion, and expression of emotion. The study then investigates the sub-factor effects on job satisfaction. A total of 353 valid questionnaires were collected. Results - The results of the path analysis showed that appraisal, utilization, and expression of emotion had a positive effect on intrinsic motivation, and utilization of emotion had a positive effect on extrinsic motivation. Extrinsic motivation had a positive effect on perceived organizational support and job satisfaction, and perceived organizational support had a positive effect on job satisfaction. Conclusion - As consultants' utilization of emotion is rendered as the ability to use emotion to improve performance, the conclusion is that such factors as monetary performance incentives are important in order to boost job satisfaction of the consultants.

• Journal of Convergence for Information Technology
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• v.11 no.11
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• pp.115-124
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• 2021

This research empirically tested the mediating role of customer emotion on the relationship between customer tumbler experience and social legitimacy. For this purpose, data were collected by surveying consumers who use tumblers. Structural equation model analysis was used for hypothesis testing, and the method proosed by Hoyle and Smith was used to additionally test the mediating effect of customer experience and social legitimacy. The empirical analysis results are as follows. First, customer experience has a positive effect on customer emotion and social legitimacy. Second, customer emotion has a positive effect on social legitimacy. This study proposes a exploratory relationship among customer tumbler experience, customer emotion, and social legitimacy and empirically shows that customer experience and customer emotion are identified as antecedents to social legitimacy.

• The Journal of the Acoustical Society of Korea
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• v.25 no.8
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• pp.375-382
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• 2006

This paper is about how to identify emotional information and how to detect a specific emotion from speech signals. For emotion identification and detection task. we use long-term acoustic feature parameters and select the optimal Parameters using the feature selection technique based on F-score. We transform the conventional SVM into probabilistic output SVM for our emotion identification and detection system. In this paper we propose three approximation methods for log-likelihoods in a hypothesis test and compare the performance of those three methods. Experimental results using the SUSAS database showed the effectiveness of both feature selection and Probabilistic output SVM in the emotion identification task. The proposed methods could detect anger emotion with 91.3% correctness.

• Journal of the Korea Computer Graphics Society
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• v.24 no.4
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• pp.1-9
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• 2018

We propose an emotional training framework that can determine the initial symptom of schizophrenia by using emotional analysis method through facial expression change. We use Emotion API in Microsoft to obtain facial expressions and emotion values at the present time. We analyzed these values and recognized subtle facial expressions that change with time. The emotion states were classified according to the peak analysis-based variance method in order to measure the emotions appearing in facial expressions according to time. The proposed method analyzes the lack of emotional recognition and expressive ability by using characteristics that are different from the emotional state changes classified according to the six basic emotions proposed by Ekman. As a result, the analyzed values are integrated into the image color transfer framework so that users can easily recognize and train their own emotional changes.

• Korean Journal of Child Studies
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• v.31 no.5
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• pp.17-30
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• 2010

The purpose of this study was to investigate the relationship between surface/deep acting in emotion labor, the collectivism and the organizational commitment of teachers in kindergartens and childcare centers. The subjects were 212 teachers employed in kindergartens or childcare centers in Daegu and Gyeongbuk Province. The collected data were analyzed by mean of Pearson's correlation, simple regression, hierarchial regression, by the use of SPSS Win 15.0. The results of our study are as follows. (1) Collectivism was positively associated with deep acting in emotion labor but not with surface acting. (2) Organizational commitment was positively associated with deep acting in emotion labor but not with surface acting. (3) Collectivism operated as a main effect with organizational commitment being observed to increase as collectivism increased. In addition, interaction effects of deep acting in emotion labor and collectivism on organizational commitment were observed, however, no interaction effects were seen in term of surface acting in emotion labor and collectivism on organizational commitment.