• Proceedings of the Korean Society for Emotion and Sensibility Conference
• /
• 2004.11a
• /
• pp.24-24
• /
• 2004

• Proceedings of the Korean Society for Emotion and Sensibility Conference
• /
• 2004.11a
• /
• pp.30-30
• /
• 2004

• International Journal of Advanced Culture Technology
• /
• v.6 no.3
• /
• pp.117-128
• /
• 2018

This study attempts to derive the possibility of literary therapy through addition and subtraction of emotional codons. It is presumed that the remnants of the emotions formed by the addition and subtraction of emotions will remain in the human body and cause chemical reactions. When this research is activated, cluster of emotional codons will be created by a combination of literary emotions. This is expected to accelerate therapeutic action of sentences by encoding certain emotional codons in AI.

• The Journal of the Korea Contents Association
• /
• v.16 no.2
• /
• pp.332-343
• /
• 2016

With the advance of digital technology, new methods which acquire color information and combine it with various contents are emerging. Color has some effect on emotion while it gives some information as component of an image. In addition, change in emotion and sensation from color stimulus makes some change in cognition. This research investigate the effect of color overlay on cognition depending on emotional state. With this goal, subjects consisting of 10 men and 10 women solved some problems with color overlay of red, orange, and green after watching short video clips which intend to induce target emotion. Experimental results show that red color overlay under positive emotion significantly reduces the average score of solving problems, while green overlay under negative emotion significantly increases it. It is also analyzed that there is not statistically significant difference in cognitive function with color overlay while it is significantly better under positive emotion than negative emotion without color overlay.

• Annual Conference on Human and Language Technology
• /
• 2004.10d
• /
• pp.191-199
• /
• 2004

본 논문에서는 텍스트에 나타난 감정상태를 인지하는 모델을 제안하고, 이러한 모델을 활용하여 현재문장에서 나타난 감정 및 이후에 나타나게 될 감정상태들을 예측하는 시스템에 대하여 다룬다. 사용자의 감정을 인지하고 이에 대한 자연스러운 메시지, 행동 등을 통해 인간과 상호작용 할 수 있는 컴퓨터시스템을 구현하기 위해서는 현재의 감정상태뿐만 아니라 사용자 개개인의 정보 및 시스템과 상호작용하고 있는 상황의 정보 등을 통해 이후에 사용자가 느낄 수 있는 감정을 예측할 수 있는 감정모델이 요구된다. 본 논문에서는 파악된 이전의 감정상태 및 실제 감정과 표현된 감정간의 관계, 그리고 감정에 영향을 미친 주변대상의 특징 및 감정경험자의 목표와 행동이 반영된 상태-전이형태의 감정모델인 감정망(Emotion Network)을 제안한다. 감정망은 각 감정을 나타내는 상태(state)와 연결된 상태들 간의 전이(transition), 그리고 전이가 발생하기 위한 조건(condition)으로 구성된다. 본 논문에서는 텍스트 형태의 상담예시에 감정망을 활용하여 문헌의 감정어휘에 의해 직접적으로 표출되지 않는 감정을 예측할 수 있음을 보인다.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.16 no.3
• /
• pp.1076-1094
• /
• 2022

Technology for emotion recognition is an essential part of human personality analysis. To define human personality characteristics, the existing method used the survey method. However, there are many cases where communication cannot make without considering emotions. Hence, emotional recognition technology is an essential element for communication but has also been adopted in many other fields. A person's emotions are revealed in various ways, typically including facial, speech, and biometric responses. Therefore, various methods can recognize emotions, e.g., images, voice signals, and physiological signals. Physiological signals are measured with biological sensors and analyzed to identify emotions. This study employed two sensor types. First, the existing method, the binary arousal-valence method, was subdivided into four levels to classify emotions in more detail. Then, based on the current techniques classified as High/Low, the model was further subdivided into multi-levels. Finally, signal characteristics were extracted using a 1-D Convolution Neural Network (CNN) and classified sixteen feelings. Although CNN was used to learn images in 2D, sensor data in 1D was used as the input in this paper. Finally, the proposed emotional recognition system was evaluated by measuring actual sensors.

• Educational Technology International
• /
• v.18 no.2
• /
• pp.101-129
• /
• 2017

This study attempted to collect learners' emotion and state motivation, analyze their inner states, and measure state motivation using a non-self-reported survey. Emotions were measured by learning segment in detailed learning situations, and they were used to indicate total state motivation with prediction power. Emotion was also used to explain state motivation by learning segment. The purpose of this study was to overcome the limitations of video-based learning environments by verifying whether the emotions measured during individual learning segments can be used to indicate the learner's state motivation. Sixty-eight students participated in a 90-minute to measure their emotions and state motivation, and emotions showed a statistically significant relationship between total state motivation and motivation by learning segment. Although this result is not clear because this was an exploratory study, it is meaningful that this study showed the possibility that emotions during different learning segments can indicate state motivation.

• MALSORI
• /
• no.62
• /
• pp.19-32
• /
• 2007

This study investigated the perception of emotional voices by transplanting some or all of the prosodic aspects, i.e. pitch, duration, and intensity, of the utterances produced with emotional voices onto those with normal voices and vice versa. Listening evaluation by 24 raters revealed that prosodic effect was greater than segmental & vocal quality effect on the preception of the emotion. The degree of influence of prosody and that of segments & vocal quality varied according to the type of emotion. As for fear, prosodic elements had far greater influence than segmental & vocal quality elements whereas segmental and vocal elements had as much effect as prosody on the perception of happy voices. Different amount of contribution to the perception of emotion was found among prosodic features with the descending order of pitch, duration and intensity. As for the length of the utterances, the perception of emotion was more effective with long utterances than with short utterances.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2005.06a
• /
• pp.1937-1943
• /
• 2005

The technology of emotion recognition is a crucial factor in day of ubiquitous that it provides various intelligent services for human. This paper intends to make the system which recognizes the human emotions based on 2-dimensional model with two bio signals, GSR and HRV. Since it is too difficult to make model the human's bio system analytically, as a statistical method, Hidden Markov Model(HMM) is used, which uses the transition probability among various states and measurable observation variance. As a result of experiments for each emotion, we can get average recognition rates of 64% for first HMM results and 55% for second HMM results

• Science of Emotion and Sensibility
• /
• v.17 no.2
• /
• pp.45-54
• /
• 2014

In recent years, advancing technology and growing interest in neuromarketing and neurobranding have led to foundational research that facilitates a better understanding of consumers' affective responses and unconscious information processing. However, the areas of aesthetics and design have remained largely unaffected by such advances and implications. The purpose of this study is to present a systematic review of the neuroscientific evidence aimed at sensible design for design and marketing researchers interested in exploring neuroaesthetics, an interdisciplinary area by nature. Sciencedirect, EBSCO, and the Google Scholar database were searched in February 2014 to select and review previous studies of aesthetics involving neuroscience. Twenty-eight studies were reviewed and divided into two categories: reward system and emotion. In addition to discussions on previous approaches, future research directions focusing on the process of aesthetic judgments (e.g., design elements, marketing stimuli) are proposed.