• Science of Emotion and Sensibility
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• v.16 no.1
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• pp.117-124
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• 2013

This study examined that how precisely MFCC, LPC, energy, and pitch related parameters of the speech data, which have been used mainly for voice recognition system could predict the vocal emotion categories as well as dimensions of vocal emotion. 110 college students participated in this experiment. For more realistic emotional response, we used well defined emotion-inducing stimuli. This study analyzed the relationship between the parameters of MFCC, LPC, energy, and pitch of the speech data and four emotional dimensions (valence, arousal, intensity, and potency). Because dimensional approach is more useful for realistic emotion classification. It results in the best vocal cue parameters for predicting each of dimensions by stepwise multiple regression analysis. Emotion categorizing accuracy analyzed by LDA is 62.7%, and four dimension regression models are statistically significant, p<.001. Consequently, this result showed the possibility that the parameters could also be applied to spontaneous vocal emotion recognition.

• Science of Emotion and Sensibility
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• v.14 no.1
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• pp.101-116
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• 2011

Current researches on emotion detection classify emotions by using the information from facial, vocal, and bodily expressions, or physiological responses. This study was to review three representative emotion recognition methods, which were based on psychological theory of emotion. Firstly, literature review on the emotion recognition methods based on facial expressions was done. These studies were supported by Darwin's theory. Secondly, review on the emotion recognition methods based on changes in physiology was conducted. These researches were relied on James' theory. Lastly, a review on the emotion recognition was conducted on the basis of multimodality(i.e., combination of signals from face, dialogue, posture, or peripheral nervous system). These studies were supported by both Darwin's and James' theories. In each part, research findings was examined as well as theoretical backgrounds which each method was relied on. This review proposed a need for an integrated model of emotion recognition methods to evolve the way of emotion recognition. The integrated model suggests that emotion recognition methods are needed to include other physiological signals such as brain responses or face temperature. Also, the integrated model proposed that emotion recognition methods are needed to be based on multidimensional model and take consideration of cognitive appraisal factors during emotional experience.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2001.05a
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• pp.225-230
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• 2001

Intensity of background noise is a factor significantly affecting both subjective evaluation of experienced stress level and associated electroencephalographic (EEG) responses during mental load in noisy environments. In the study on 27 subjects we analyzed the influence of the background white noise (WN) intensity on psychophysiological responses during a word recognition test. Electrocortical activity were recorded during baseline resting state and 40 s long performance on 3 similar Korean word recognition tests with different intensities of background WN (55, 70 and 85 dB).. An important finding in terms of physiological reactivity was similarity of all physiological response profiles between 55 and 70dB WN, i.e., none of physiological variables differentiated the two conditions, while 85dB WN resulted in a significantly different profile of reactions (higher fast beta power in EEG spectra). This condition was characterized by highest subjective rating of experienced stress, had more fast beta activity and had tendency of right hemisphere dominance, emphasizing the role of brain lateralization in negative affect control.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 1998.11a
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• pp.273-277
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• 1998

The purpose of this study was to develop a large representative data base for jeans marketing strategy. This study was to survey brand awareness and analyze brand image and consumer's seeking image. The 700 questionnaires were distributed and 656 reliable ones were used for statistical analysis. A SAS statistical package including frequency table, factor analysis, analysis of variance, Duncan's multiple range test, Peason's correlation test was used. The results are as follows: 1. Brand awareness involves "brand recall" based on asking a person to name recalled first, and "brand recognition" based on asking to identify brand name from 30 given brands. The result indicated that "Levi" was dominant for brand recall and Guess was dominant for brand recognition. 2. Regarding the brand image, the result showed that "Vov" was best represented for sophisticated 8t trendy brand images, "Storm" for sophisticated brand image, "Jambangee" for reasonable price & comfortable brand images, and "Levis" for classic & design/color brand images. 3. As a result of factor analysis on consumer's seeking image, six factors(characteristic/gay, intelligent/sexy, feminine/sophisticated, active/functional, cute/young, simple/comfortable) were found. Several factors had a relationship with demographic variables, preferred design, fashion interest.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2002.05a
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• pp.266-269
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• 2002

This paper explores a fundamental study of acquiring the users' KANSEI information regarding the recognition of shape models. Since there are many differences such as background differences and knowledge differences among users, they will produce different evaluations based on their KANSEI even when an identical shape model is presented. Cluster analysis is proved to be available for catching a group tendency and for constructing a mapping relation between a description of the shape model and the HANSEl database. In order to investigate an analogical relation and a mutual influence in our consciousness, first, we made a questionnaire that asked subjects to represent images having different colors and shape cones by using 4 pairs of adjectives (KANSEI words). Next, based on the cluster analysis of the questionnaire using a fuzzy set theory, we proposed a hypothesis showing how the analogical relation and the mutual influence work in our mind while viewing the shape models. Furthermore, how the properties of KANSEI depend on their descriptions was also investigated by virtue of the cluster analysis. This work will be valuable to construct a personal KANSEI database regarding the Shape Model Processing System.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2009.05a
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• pp.67-70
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• 2009

본 논문에서는 생리신호를 이용한 감성인식의 정확도를 높이기 위한 개인화 방안에 대해 연구하였다. 이전연구 결과인 TDP(Time Dependent Parameters)를 이용한 감성인식방법은 자율신경계 반응을 4 단계로 세분화하여 감성인식의 정확도를 높일 수 있었다. 하지만 평균 정확도는 향상된 반면 개인별로 정확도의 개인차가 발생하였다. 본 연구는 개인차를 줄이기 위해서, 개인의 반응에 따라 감성인식을 위한 룰베이스가 변화하는 적응적 TDP 알고리즘을 개발하였다. 시각자극을 이용한 감성유발 실험결과를 분석하여 감성인식 개인차가 감소하였는지 확인하였다. 실험은 4 명을 대상으로 하였으며 한 명당 24번의 시각 자극을 제시하여 96개의 데이터가 수집되었다. 데이터는 자율신경계 반응과 주관적 감성을 측정하였나 TDP 를 이용한 분석과 적응적 TDP 분석방법으로 감성을 인식한 결과를 비교한 결과 평균 정확도는 증가하지 않았지만 전반적인 정확도 수준은 상승하는 것을 확인하였다. 그러므로 적응적 TDP를 이용할 경우 개인차를 줄일 수 있다는 것을 확인하였다.

• Science of Emotion and Sensibility
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• v.20 no.4
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• pp.101-112
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• 2017

We investigated the neural representation of reward probability recognition and its neural connectivity with other regions of the brain. Using functional magnetic resonance imaging (fMRI), we used a simple guessing task with different probabilities of obtaining rewards across trials to assay local and global regions processing reward probability. The results of whole brain analysis demonstrated that lateral prefrontal cortex, inferior parietal lobe, and postcentral gyrus were activated during probability-based decision making. Specifically, the higher the expected value was, the more these regions were activated. Fronto-parietal connectivity, comprising inferior parietal regions and right lateral prefrontal cortex, conjointly engaged during high reward probability recognition compared to low reward condition, regardless of whether the reward information was extrinsically presented. Finally, the result of a regression analysis identified that cortico-subcortical connectivity was strengthened during the high reward anticipation for the subjects with higher cognitive impulsivity. Our findings demonstrate that interregional functional involvement is involved in valuation based on reward probability and that personality trait such as cognitive impulsivity plays a role in modulating the connectivity among different brain regions.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.4
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• pp.157-163
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• 2014

User's sensitivity is recognized as a very important parameter for communication between company, government and personnel. Especially in many studies, researchers use voice tone, voice speed, facial expression, moving direction and speed of body, and gestures to recognize the sensitivity. Multiplex modality is more precise than single modality however it has limited recognition rate and overload of data processing according to multi-sensing also an excellent algorithm is needed to deduce the sensing value. That is as each modality has different concept and property, errors might be happened to convert the human sensibility to standard values. To deal with this matter, the sensibility expression modality is needed to be extracted using technologies like analyzing of relational network, understanding of context and digital filter from multiplex modality. In specific situation to recognize the sensibility if the priority modality and other surrounding modalities are processed to implicit values, a robust system can be composed in comparison to the consuming of computer resource. As a result of this paper, it is proposed how to assign the weight of multiplex modality using implicit data.

• Science of Emotion and Sensibility
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• v.20 no.1
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• pp.75-82
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• 2017

We propose a novel method for modeling emotional dimensions using expansion of Russell's (1980) emotional dimensions (Circumplex Model). The Circumplex Model represents emotional words in two axes (Arousal, Valence). However, other researchers have insisted that location of word in Russell's model which is expressed by single point could not represent exact position. Consequently, it is difficult to apply this model in engineering fields (such as Science of Emotion & Sensibility, Human-Computer-Interaction, Ergonomics, etc.). Therefore, we propose a new modeling method which expresses emotional word not as a single point but as a region. We conducted survey to obtain actual data and derived equations using ellipse formula to represent emotional region. Furthermore, we applied ANEW and IAPS which are commonly used in many studies to our emotional model using pattern recognition algorithm. Using our method, we could solve problems with Russell's model and our model is easily applicable to the field of engineering.

• Journal of Digital Contents Society
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• v.18 no.3
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• pp.465-473
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• 2017

An experiment was conducted to investigate the relationship between the DVEs and subtitles provided with anchor speech in TV news and the news evaluation, trust and agenda recognition. 120 university students were asked to watch four types of news that differed in the contents of their DVEs and subtitles, and then they evaluated the fairness, sensibility, and irritability of the news. The content of DVEs and subtitles were related to the irritability evaluation and trust of the news, and it was not related with the fairness and sensibility evaluation. When the DVEs and subtitles emphasizing the stimulating aspects of the issue were given, the irritability was highly evaluated and the trust was low. The evaluation on news fairness affected the news trust. The more they rated news as fair, the greater the trust in news. Unlike the assumption in this study, DVEs and subtitles were not the main factors influencing the news agenda perception, and the viewers tended to perceive the agenda based on the news content itself.