• Proceedings of the Acoustical Society of Korea Conference
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• autumn
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• pp.93-96
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• 1999

감정을 표현하는 음성 합성 시스템을 구현하기 위해서 이전 논문에서는 음운 및 운율 요소(피치, 에너지, 지속시간, 스펙트럼 인벨로프)가 각 감정 음성에 미치는 영향에 대한 분석을 수행하였다. 본 논문에서는 네 가지 감정 표현(평상, 화남, 기쁨, 슬픔)을 나타내는 음성 데이터에 대해 음절 세그먼트와 라벨링을 행한 감정 음성 데이터베이스를 토대로 감정 표현에 많은 영향을 미치는 요소인 피치가 어떻게 변화하는지를 분석하였다. 통계적인 방법을 이용하여 감정별 피치를 정규화 하였으며, 감정 음성 데이터베이스 내의 문장별 피치 패턴에 대해 분석하였다. 그 결과 감정별 피치의 평균 ZScore는 화남이 가장 작았으며, 기쁨, 평상, 슬픔의 순으로 높았다. 또한 감정별 피치의 범위 변화는 슬픔이 가장 작았으며, 평상, 화남, 기쁨의 순으로 높았다. 문장별 피치의 패턴은 감정 표현에 따라 전체적으로 대부분 유사하게 나타났으며, 문장의 처음 부분은 화남의 경우 다른 감정에 비해 대체로 높게 변화하였고, 화남과 기쁨의 경우 문장의 뒷부분에서 다른 감정에 비해 피치가 상승하는 것을 볼 수 있었다.

• Annual Conference on Human and Language Technology
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• 2018.10a
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• pp.91-94
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• 2018

감정분석은 텍스트에서 나타난 저자 혹은 발화자의 태도, 의견 등과 같은 주관적인 정보를 추출하는 기술이며, 여론 분석, 시장 동향 분석 등 다양한 분야에 두루 사용된다. 감정분석 방법은 사전 기반 방법, 기계학습 기반 방법 등이 있다. 본 논문은 사전 기반 감정분석에 필요한 한국어 감정사전 자동 구축 방법을 제안한다. 본 논문은 영어 감정사전으로부터 한국어 감정사전을 자동으로 구축하는 방법이며, 크게 세 단계로 구성된다. 첫 번째는 영한 병렬말뭉치를 이용한 영한사전을 구축하는 단계이고, 두 번째는 영한사전을 통한 이중언어 그래프를 생성하는 단계이며, 세 번째는 영어 단어의 감정값을 한국어 단어의 감정값으로 전파하는 단계이다. 본 논문에서는 제안된 방법의 유효성을 보이기 위해 사전 기반 한국어 감정분석 시스템을 구축하여 평가하였으며, 그 결과 제안된 방법이 합리적인 방법임을 확인할 수 있었으며 향후 연구를 통해 개선한다면 질 좋은 한국어 감정사전을 효과적인 방법으로 구축할 수 있을 것이다.

• 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.

• 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.

• The Journal of Society for e-Business Studies
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• v.19 no.4
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• pp.1-19
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• 2014

Efforts to identify user's recognition which exists in the big data are being conducted actively. They try to measure scores of people's view about products, movies and social issues by analyzing statements raised on Internet bulletin boards or SNS. So this study deals with the problem of determining how to find the emotional vocabulary and the degree of these values. The survey methods are using the results of previous studies for the basic emotional vocabulary and degree, and inferring from the dictionary's glosses for the extended emotional vocabulary. The results were found to have the 4 emotional words lists (vocabularies) as basic emotional list, extended 1 stratum 1 level list from basic vocabulary's glosses, extended 2 stratum 1 level list from glosses of non-emotional words, and extended 2 stratum 2 level list from glosses' glosses. And we obtained the emotional degrees by applying the weight of the sentences and the emphasis multiplier values on the basis of basic emotional list. Experimental results have been identified as AND and OR sentence having a weight of average degree of included words. And MULTIPLY sentence having 1.2 to 1.5 weight depending on the type of adverb. It is also assumed that NOT sentence having a certain degree by reducing and reversing the original word's emotional degree. It is also considered that emphasis multiplier values have 2 for 1 stratum and 3 for 2 stratum.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.5
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• pp.251-264
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• 2022

Previous researches related to emotional labor have been cross-sectional studies focusing on static differences in emotional exhaustion. Previous studies on these relationships have not highlighted the dynamic properties of these relationships. This purpose of this study is to investigate the effect of emotional labor strategy on perceived emotional exhaustion and depression. This study was conducted by paying attention to the fact that service industry workers who have to respond kindly to customers often have to show emotions which is necessary for their business to the outside world rather than showing their true emotions. The results of this study are summarized as follows. First, it was confirmed that surface acting had a positive influence on emotional exhaustion, but deep acting had a negative influence to emotional exhaustion. Second, it was found that surface acting had a positive influence on depression, but deep acting had a negative influence on depression. Third, it was confirmed that the effect of deep acting on emotional exhaustion decreased when emotional labor was performed through deep acting on Mondays, Tuesdays, and Wednesdays, while emotional exhaustion was not significant on Thursdays and Fridays. Fourth, it was confirmed that the difference in the effect of emotional labor strategy on depression was greater in the case of performing emotional labor through surface acting than in the case of performing emotional labor through deep acting.

• Cartoon and Animation Studies
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• s.15
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• pp.179-192
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• 2009

This study investigates the effects of empathy responses towards animated spokes-characters in advertising on brand likability. This study also examines the mediating role of cognitive and affective responses towards character advertising in the effect process of empathy. Statistically, several significant results are found. First, empathy has positive effects on cognitive responses and affective responses. Second, both cognitive and affective responses have positive influence on brand likability, but the effects of cognitive responses show relatively weaker than those of affective responses. Third, empathy has a positive influence on brand likability mediated by cognitive responses, but affective responses as a mediator do not show statistically significant differences. The results of this study indicate consumers can have emotional responses to advertising characters just as they do to human information sources. And the results also imply that enhancement of the empathy intensity should be considered to make effective animated characters in advertising, and that advertising appeals should be practiced to form cognitive responses positively and strongly to strengthen consumers' empathy responses.

• Culinary science and hospitality research
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• v.17 no.3
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• pp.104-116
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• 2011

This study examines the effect of culinary employees' emotional labor on their emotional dissonance and turnover intentions and bow the emotional labor and emotional dissonance affect their turnover intentions and burnout to provide useful information and suggestions for the foodservice and hotel culinary training and on-site. The results are summarized as follows. First, as the emotional labor of workers such as representation of the act, conduct in-depth and emotional departure grew higher, they showed the higher perception of emotional dissonance. However, their spontaneous activities tended to decrease their emotional dissonance. Second, as the result of verifying the relationship between emotional dissonance and burnout, the higher emotional dissonance, the deeper burnout. Finally, the culinary workers' emotional dissonance influenced their turnover intention.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.2
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• pp.53-60
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• 2020

Sentiment analysis is the automated process of understanding attitudes and opinions about a given topic from written or spoken text. One of the sentiment analysis approaches is a dictionary-based approach, in which a sentiment dictionary plays an much important role. In this paper, we propose a method to automatically generate Korean sentiment lexicon from the well-known English sentiment lexicon called VADER (Valence Aware Dictionary and sEntiment Reasoner). The proposed method consists of three steps. The first step is to build a Korean-English bilingual lexicon using a Korean-English parallel corpus. The bilingual lexicon is a set of pairs between VADER sentiment words and Korean morphemes as candidates of Korean sentiment words. The second step is to construct a bilingual words graph using the bilingual lexicon. The third step is to run the label propagation algorithm throughout the bilingual graph. Finally a new Korean sentiment lexicon is generated by repeatedly applying the propagation algorithm until the values of all vertices converge. Empirically, the dictionary-based sentiment classifier using the Korean sentiment lexicon outperforms machine learning-based approaches on the KMU sentiment corpus and the Naver sentiment corpus. In the future, we will apply the proposed approach to generate multilingual sentiment lexica.

• Journal of the Korea Society of Computer and Information
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• v.19 no.11
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• pp.159-166
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• 2014

In this paper, we examine the role of emotional acoustic cues including both prosody and voice quality parameters for the modification of a word sense. For the extraction of prosody parameters and voice quality parameters, we used 60 pieces of speech data spoken by six speakers with five different emotional states. We analyzed eight different emotional acoustic cues, and used a discriminant analysis technique in order to find the dominant sequence of acoustic cues. As a result, we found that anger has a close relation with intensity level and 2nd formant bandwidth range; joy has a relative relation with the position of 2nd and 3rd formant values and intensity level; sadness has a strong relation only with prosody cues such as intensity level and pitch level; and fear has a relation with pitch level and 2nd formant value with its bandwidth range. These findings can be used as the guideline for find-tuning an emotional spoken language generation system, because these distinct sequences of acoustic cues reveal the subtle characteristics of each emotional state.