• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.165-166
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• 2013

The principle of human perception, behavior, and thought is presented in the traditional interface design study that is ease to use and increase the learn-ability. We believe that the usability is related to user's affection. The goal of this paper is to investigate how visual metaphor works in usability and affection in interface to analyse the effect of visual metaphor to user affection. Literature reviews for the concept of metaphor and affection design conducted. We analyse the effect to user's affection through think-aloud i.e. protocol analysis for metaphor.

• Proceedings of the Korean Society of Computer Information Conference
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• 2016.07a
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• pp.17-20
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• 2016

딥러닝 기법이 발달함에 따라 텍스트에 내재된 의미 및 구문을 어떠한 벡터 공간 상에 표현하기 위한 언어 모델이 활발히 연구되어 왔다. 이를 통해 자연어 처리를 기반으로 하는 감성 분석 및 문서 분류, 기계 번역 등의 분야가 진보되었다. 그러나 대부분의 언어 모델들은 텍스트에 나타나는 단어들의 일반적인 패턴을 학습하는 것을 기반으로 하기 때문에, 문서 요약이나 스토리텔링, 의역된 문장 판별 등과 같이 보다 고도화된 자연어의 이해를 필요로 하는 연구들의 경우 주어진 텍스트의 주제 및 의미를 고려하기에 한계점이 있다. 이와 같은 한계점을 고려하기 위하여, 본 연구에서는 기존의 LSTM 모델을 변형하여 문서 주제와 해당 주제에서 단어가 가지는 문맥적인 의미를 단어 벡터 표현에 반영할 수 있는 새로운 언어 학습 모델을 제안하고, 본 제안 모델이 문서의 주제를 고려하여 문장을 자동으로 생성할 수 있음을 보이고자 한다.

• Annual Conference on Human and Language Technology
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• 2020.10a
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• pp.172-175
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• 2020

최근 자연어처리는 대용량 코퍼스를 이용하여 언어 모델을 사전 학습하고 fine-tuning을 적용함으로 다양한 태스크에서 최고 성능을 갱신하고 있다. BERT기반의 언어 모델들은 양방향의 Transformer만 모델링 되어 있지만 BART는 양방향의 Transformer와 Auto-Regressive Transformer가 결합되어 사전학습을 진행하는 모델로 본 논문에서는 540MB의 코퍼스를 이용해 한국어 BART 모델을 학습 시키고 여러 한국어 자연어처리 태스크에 적용하여 성능 향상 있음을 보였다.

• Science of Emotion and Sensibility
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• v.9 no.1
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• pp.9-17
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• 2006

As is commonly said, music is 'language of emotions.' It is because sound is a plentiful modality to communicate the human sensibility information. However, most researches of auditory displays were focused on improving efficiency on user's performance data such as performance time and accuracy. Recently, many of researchers in auditory displays acknowledge that individual preference and sensible satisfaction may be a more important factor than the performance data. On this ground, in the present study we constructed the sound sensibility dimensions ('Pleasure', 'Complexity', and 'Activity') and systematically examined the attributes of sound on the sensibility dimensions and analyzed the meanings. As a result, sound sensibility dimensions depended on each sound attributes , and some sound attributes interact with one another. Consequently, the results of the present study will provide the useful possibilities of applying the affective influence in the field of auditory displays needing the applications of the sensibility information according to the sound attributes.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.6
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• pp.3858-3864
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• 2014

This paper proposes the smart emotion lighting control system of a mobile-based. The proposed smart emotional lighting control system to reduce the emotional lighting device, internal heat and the power consumption was configured to the android platform mobile device and zigbee module, emotional lighting device, lighting control module, power supply, and general-purpose transistor. The mobile device was to transmit the real-time control information to the emotional lighting device when connected to the system, and it was designed to control the emotion lighting device based on the control messages and status monitoring. In this paper, the efficiency verification results of the proposed smart emotional lighting control system showed that it was possible to control by emotion lighting control and the color temperature variable. The heating value and the power consumption could be reduced by21% and up to 48%, because of the controlled lighting using emotion language.

• Archives of design research
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• v.17 no.1
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• pp.319-328
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• 2004

The communication environment made by digital technologies has made it possible to exchange information and deliver messages fast and easily among people of various classes in virtual space beyond time and space. Net-generation, who is accustomed to this virtual space, couldn't be satisfied with the linear text-oriented language any more, and began to make signs by use of computers in order to differentiate itself from others and to express its desires. Among the signs, emoticon created by joint of popular culture and digital communication centering around young generation is a new visual sign and emotional sign that can deliver a sender's feelings contained in a message. This paper has studied social phenomena, their relationships with emoticon and background of its creation through documentary review of media development, changes in the communication environment and popular culture. Furthermore, it has analyzed the meaningful action and roles of emoticon as a sign in terms of semiotics and also, studied a possibility of using emoticon as a new emotional sign. The study results say that emoticon can play the roles of a non-linguistic sign just like general signs that make mutual exchange through meaningful action, and also that it can be used to effectively deliver messages not only in virtual space, but also in advertising, posters, magazines and CI. However, emoticon is better at emotional expressions yet than other textual signs or visual signs, but in order to position itself as a universal and popular sign, emotional expressions should be clear, any difference in understanding messages should be removed, and message delivery should be more efficient.

• Annual Conference on Human and Language Technology
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• 2019.10a
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• pp.400-403
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• 2019

스타일 변환(Style Transfer)은 주어진 문장의 긍정이나 부정 같은 속성을 변경하여 다른 속성을 갖는 문장으로 변환하는 과정을 의미한다. 본 연구에서는 스타일 변환을 위한 단어 n-그램 삭제의 기준을 확장하였고, 네이버 영화리뷰 데이터셋을 통해 이를 스타일 변환 이후 원래 문장의 스타일로부터 얼마나 차이가 나게 되었는지를 측정하였다. 측정은 감성분석기를 통해 이루어졌고, 기존 방법에 비해 6.28%p정도 높은 75.13%의 정확도를 보였다.

• Science of Emotion and Sensibility
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• v.22 no.3
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• pp.35-46
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• 2019

Artificial intelligence (AI) technology has been evolving to recognize and learn the languages, voice tones, and facial expressions of users so that they can respond to users' emotions in various contexts. Many AI-based services of particular importance in communications with users provide emotional interaction. However, research on nonverbal interaction as a means of expressing emotion in the AI system is still insufficient. We studied the effect of lighting on users' emotional interaction with an AI device, focusing on color and flickering motion. The AI device used in this study expresses emotions with six colors of light (red, yellow, green, blue, purple, and white) and with a three-level flickering effect (high, middle, and low velocity). We studied the responses of 50 men and women in their 20s and 30s to the emotions expressed by the light colors and flickering effects of the AI device. We found that each light color represented an emotion that was largely similar to the user's emotional image shown in a previous color-sensibility study. The rate of flickering of the lights produced changes in emotional arousal and balance. The change in arousal patterns produced similar intensities of all colors. On the other hand, changes in balance patterns were somewhat related to the emotional image in the previous color-sensibility study, but the colors were different. As AI systems and devices are becoming more diverse, our findings are expected to contribute to designing the users emotional with AI devices through lighting.

• Journal of the Korean Institute of Intelligent Systems
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• v.9 no.5
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• pp.526-537
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• 1999

In the paper. we propose an evaluation model based the adaptive fuzzy systems, which can transform the physical features of a color pattern to the emotional features. The model is motivated by the Soen's psychological experiments, in which he found the physical features such as average hue, saturation, intensity and the dynamic components of the color patterns affects to the emotional features represented by a pair of adjective words having the opposite meanings. Our proposed model consists of two adaptive fuzzy rule-bases and the y-model, a l i r ~ r ys et operator, to fuze the evaluation values produced by them. The model shows con~parablep erformances to the neural network for the approximation of the nonlinear transforms, and it has the advantage to obtain the linbwistic interpretation from the trained results. We believe the evaluated results of a color pattern can be used to the emotion-based color image retrievals.

• Smart Media Journal
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• v.13 no.6
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• pp.44-53
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• 2024

Companies in modern society are increasingly recognizing sentiment classification as a crucial task, emphasizing the importance of accurately understanding consumer opinions opinions across various platforms such as social media, product reviews, and customer feedback for competitive success. Extensive research is being conducted on sentiment classification as it helps improve products or services by identifying the diverse opinions and emotions of consumers. In sentiment classification, fine-tuning with large-scale datasets and pre-trained language models is essential for enhancing performance. Recent advancements in artificial intelligence have led to high-performing sentiment classification models, with the ELECTRA model standing out due to its efficient learning methods and minimal computing resource requirements. Therefore, this paper proposes a method to enhance sentiment classification performance through efficient fine-tuning of various datasets using the KoELECTRA model, specifically trained for Korean.