• 대한음성학회지:말소리
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• 제54호
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• pp.45-61
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• 2005

In this paper, we present a method of generating intonation contour for Korean text-to-speech (TTS) system and a method of synthesizing emotional speech, both based on Soft template mark-up language (Stem-ML), a novel prosody generation model combining mark-up tags and pitch generation in one. The evaluation shows that the intonation contour generated by Stem-ML is better than that by our previous work. It is also found that Stem-ML is a useful tool for generating emotional speech, by controling limited number of tags. Large-size emotional speech database is crucial for more extensive evaluation.

• Journal of Information Technology Applications and Management
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• 제21권3호
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• pp.65-77
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• 2014

Ubiquitous learning has aroused great interest and is becoming a new way for foreign language education in today's society. However, how to increase the learners' initiative and their community cohesion is still an issue that deserves more profound research and studies. Emotional intelligence can help to detect the learner's emotional reactions online, and therefore stimulate his interest and the willingness to participate by adjusting teaching skills and creating fun experiences in learning. This is, actually the new concept of smart education. Based on the previous research, this paper concluded a neural mechanism model for analyzing the learners' emotional characteristics in ubiquitous environment, and discussed the intelligent monitoring and automatic recognition of emotions from the learners' speech signals as well as their behavior data by multi-agent system. Finally, a framework of emotional intelligence system was proposed concerning the smart foreign language education in ubiquitous learning.

• 센서학회지
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• 제30권6호
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• pp.429-435
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• 2021

In this study, the creation of emotional dialogue was investigated within the process of developing a robot's natural language understanding and emotional dialogue processing. Unlike an English-based dataset, which is the mainstay of natural language processing, the Korean-based dataset has several shortcomings. Therefore, in a situation where the Korean language base is insufficient, the Korean dataset should be dealt with in detail, and in particular, the unique characteristics of the language should be considered. Hence, the first step is to base this study on a specific Korean dataset consisting of conversations on emotional topics. Subsequently, a model was built that learns to extract the continuous dialogue features from a pre-trained language model to generate sentences while maintaining the context of the dialogue. To validate the model, a chatbot system was implemented and meaningful results were obtained by collecting the external subjects and conducting experiments. As a result, the proposed model was influenced by the dataset in which the conversation topic was consultation, to facilitate free and emotional communication with users as if they were consulting with a chatbot. The results were analyzed to identify and explain the advantages and disadvantages of the current model. Finally, as a necessary element to reach the aforementioned ultimate research goal, a discussion is presented on the areas for future studies.

• The Journal of Asian Finance, Economics and Business
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• 제9권2호
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• pp.395-407
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• 2022

This study examines the emotional undercurrents of individual investors. Earlier finance theory was based on the assumption that investors would act rationally. According to the findings, it is the investors' collective expectations and anxieties that have an impact on their investment fortunes. This necessitates a high level of emotional stability on the side of the investors. Investors must have a firm foundation in financial literacy to have the requisite level of emotional stability. This study aims to add to existing theory and practice by analyzing whether investors who have received business-related education are less emotional than those who have not. For the survey inquiry of individual investors, 'fear' and 'love' are considered among the emotional undercurrents of individual investors. The research is based on a survey of 875 individual investors in India, 342 of whom had a business background and the others have none. It has been discovered that no investor, regardless of their level of business education, is emotion-free. Investors with and without a business education display emotional stability in many behavioral aspects of fear and love to varying degrees.

• Journal of Electrical Engineering and Technology
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• 제8권3호
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• pp.478-489
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• 2013

The controllability and stability of power systems can be increased by Flexible AC Transmission Devices (FACTs). One of the FACTs devices is Interline Power-Flow Controller (IPFC) by which the voltage stability, dynamic stability and transient stability of power systems can be improved. In the present paper, the convenient operation and control of IPFC for transient stability improvement are considered. Considering that the system's Lyapunov energy function is a relevant tool to study the stability affair. IPFC energy function optimization has been used in order to access the maximum of transient stability margin. In order to control IPFC, a Brain Emotional Learning Based Intelligent Controller (BELBIC) and PI controller have been used. The utilization of the new controller is based on the emotion-processing mechanism in the brain and is essentially an action selection, which is based on sensory inputs and emotional cues. This intelligent control is based on the limbic system of the mammalian brain. Simulation confirms the ability of BELBIC controller compared with conventional PI controller. The designing results have been studied by the simulation of a single-machine system with infinite bus (SMIB) and another standard 9-buses system (Anderson and Fouad, 1977).

• 한국음향학회지
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• 제40권5호
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• pp.523-529
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• 2021

본 논문에서는 감정 마크업을 포함하는 Speech Synthesis Markup Language(SSML) 처리기를 설계하고 개발하였다. 다양한 음색과 감정 표현이 가능한 음성합성 기술이 개발되고 있으며 다양한 음색 및 감정 음성합성의 응용 확대를 위하여 표준화된 음성 인터페이스 마크업 언어인 SSML을 감정 표현이 가능하도록 확장한 감정 SSML(Emotional SSML)을 설계하였다. 감정 SSML 처리기는 그래픽 사용자 인터페이스로 손쉽게 음색 및 감정을 원하는 텍스트 부분에 표시할 수 있는 다음색 감정 텍스트 편집기, 편집 결과를 감정 SSML 문서로 생성하는 감정 SSML 문서 생성기, 생성된 감정 SSML 문서를 파싱하는 감정 SSML 파서, 감정 SSML 파서의 결과인 다음색 감정 합성 시퀀스를 기반으로 합성기와 연동하여 음성 스트림의 합성 을 제어하는 시퀀서로 구성된다. 본 논문에서 개발한 다음색 감정합성을 위한 감정 SSML 처리기는 프로그래밍 언어 및 플랫폼 독립적인 개방형 표준인 SSML을 기반으로 하여 다양한 음성합성 엔진에 쉽게 연동할 수 있는 구조를 가지며 다양한 음색과 감정 음성합성이 필요한 다양한 응용 개발에 활용될 것으로 기대한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권11호
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• pp.4662-4679
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• 2015

Currently, the leakage of internal information has emerged as one of the most significant security concerns in enterprise computing environments. Especially, damage due to internal information leakage by insiders is more serious than that by outsiders because insiders have considerable knowledge of the system's identification and password (ID&P/W), the security system, and the main location of sensitive data. Therefore, many security companies are developing internal data leakage prevention techniques such as data leakage protection (DLP), digital right management (DRM), and system access control, etc. However, these techniques cannot effectively block the leakage of internal information by insiders who have a legitimate access authorization. The security system does not easily detect cases which a legitimate insider changes, deletes, and leaks data stored on the server. Therefore, we focused on the insider as the detection target to address this security weakness. In other words, we switched the detection target from objects (internal information) to subjects (insiders). We concentrated on biometrics signals change when an insider conducts abnormal behavior. When insiders attempt to leak internal information, they appear to display abnormal emotional conditions due to tension, agitation, and anxiety, etc. These conditions can be detected by the changes of biometrics signals such as pulse, temperature, and skin conductivity, etc. We carried out experiments in two ways in order to verify the effectiveness of the emotional recognition technology based on biometrics signals. We analyzed the possibility of internal information leakage detection using an emotional recognition technology based on biometrics signals through experiments.

• 한국정보전자통신기술학회논문지
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• 제8권6호
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• pp.544-550
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• 2015

현재, SNS으로 소통되는 의견들이 증가하고 있기 때문에 SNS 메시지로부터 의미 있는 정보를 유추해내는 오피니언 마이닝(Opinion mining) 기술이 중요해지고 있다. 본 논문은 반의어와 부사의 위치에 따라 가중치를 다르게 설정하여 SNS의 감성 정보를 정확하게 추출하는 오피니언 마이닝 기반 SNS 감성 정보 분석 전략(SEIAS, SNS Emotional Information Analysis Strategy)을 제안한다. 제안하는 SEIAS(SNS Emotional Information Analysis Strategy)는 첫째, 오피니언 마이닝 분석에 필요한 감성사전을 구축하고, 둘째, SNS 데이터를 실시간으로 수집하고, 수집된 SNS 데이터와 감성사전를 비교하여 SNS 데이터의 의견값을 산출한다. 특히, 데이터의 의견값을 산출할 때, 반의어, 부사의 위치에 따라 가중값을 다르게 설정함으로써 기존의 SO-PMI와 비교하였을 때 오피니언 분석결과의 정확도를 향상시켰다.

• 문화기술의 융합
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• 제5권3호
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• pp.79-84
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• 2019

본 연구는 종합병원의 환경색채가 사용자의 심리적, 감성적 부분에 영향을 미칠 것이라는 가설 하에, 종합병원 로비의 환경색채에 대한 감성평가를 실시하였다. 이를 통하여 종합병원 환경색채 계획 시 보다 긍정적이고 심리적 만족감을 주는 환경색채의 요건을 고찰하고자 하는 목적을 가진다. 이를 위하여 국내 대형종합병원 8곳을 직접 방문하여 환경색채를 측색하였으며, 이를 기반으로 색채팔레트를 만들어 감성어휘평가를 실시하였다. 그 결과, 환경색채 감성평가에 영향을 미치는 색채요소 중 명도의 영향이 큰 것으로 나타났고, 명도, 채도의 범위의 편차가 클수록 감성반응에 부정적 영향을 미치는 것으로 파악되었다.

• 한국결정성장학회지
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• 제31권1호
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• pp.43-54
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• 2021

본 연구는 제품 개발의 소재 적용에 있어 트렌드 리서치를 기반으로 하는 감성 소재의 요소를 도출하는 프로세스를 제안하였다. 케이스 모델인 한국형 스포츠 휠체어 개발에 적용하고자 하였으며, CMF(Color, Material, Finish) 기반의 리서치 중 소재 부분에 초점을 맞추어 연구하였다. 메가트렌드, 경쟁사 제품 및 파트별 분석, 심리 색채 분석 등 리서치 방법론을 통해 소재 적용의 최적화 및 검증, DB화를 연구하였으며 FGI 검증을 통한 최종 적용안을 도출하였다.