• The KIPS Transactions:PartB
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• v.10B no.6
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• pp.579-586
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• 2003

In this paper, we propose a novel approach to employ emotional features to document retrieval systems. Fine emotional features, such as HAPPY, SAD, ANGRY, FEAR, and DISGUST, have been used to represent Korean document. Users are allowed to use these features for retrieving their documents. Next, retrieved documents are learned by classification methods like cohesion factor, naive Bayesian, and, k-nearest neighbor approaches. In order to combine various approaches, voting method has been used. In addition, k-means clustering has been used for our experimentation. The performance of our approach proved to be better in accuracy than other methods, and be better in short texts rather than large documents.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2252-2255
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• 2003

인간과 인공생명체(Artificial Life Systems)가 서로 커뮤니케이션을 진행하기 위하여 인공생명체는 자신이 의도한 바를 음성, 표정, 행동 등 다양한 방식을 통하여 표현할 수 있어야 한다. 특히 자신의 좋아함과 싫음 등 자율적인 감정을 표현할 수 있는 것은 인공생명체가 더욱 지능적이고 실제 생명체의 특성을 가지게 되는 중요한 전제조건이기도 하다. 위에서 언급한 인공생명체의 감정표현 특성을 구현하기 위하여 본 논문에서는 음성 속에 감정을 포함시키는 방법을 제안한다. 먼저 인간의 감정표현 음성데이터를 실제로 구축하고 이러한 음성데이터에서 감정을 표현하는데 사용되는 에너지, 지속시간, 피치(pitch) 등 특징을 추출한 후, 일반적인 음성에 위 과정에서 추출한 감정표현 특징을 적용하였으며 부가적인 주파수대역 필터링을 통해 기쁨, 슬픔, 화남, 두려움, 혐오, 놀람 등 6가지 감정을 표현할 수 있게 하였다. 감정표현을 위한 음성처리 알고리즘은 현재 음성합성에서 가장 널리 사용되고 있는 TD-PSOLA[1] 방법을 사용하였다.

• The Journal of the Korea Contents Association
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• v.6 no.3
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• pp.125-134
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• 2006

The purpose of this paper is constructed a HEEAAS(Human Emotional Expression Animaion System), which is an animation system to show both the face and the body motion from the inputted voice about just 4 types of emotions such as fear, dislike, surprise and normal. To implement our paper, we chose the korean young man in his twenties who was to show appropriate emotions the most correctly. Also, we have focused on reducing the processing time about making the real animation in making both face and body codes of emotions from the inputted voice signal. That is, we can reduce the search time to use the binary search technique from the face and body motion databases, Throughout the experiment, we have a 99.9% accuracy of the real emotional expression in the cartoon animation.

• The KIPS Transactions:PartB
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• v.18B no.5
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• pp.305-314
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• 2011

Research into the visual perception of human emotion to recognize an intention has traditionally focused on emotions of facial expression. Recently researchers have turned to the more challenging field of emotional expressions through body posture or activity. Proposed work approaches recognition of basic emotional categories from body postures using neural model applied visual perception of neurophysiology. In keeping with information processing models of the visual cortex, this work constructs a biologically plausible hierarchy of neural detectors, which can discriminate 6 basic emotional states from static views of associated body postures of activity. The proposed model, which is tolerant to parameter variations, presents its possibility by evaluating against human test subjects on a set of body postures of activities.

• Annual Conference on Human and Language Technology
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• 2008.10a
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• pp.145-150
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• 2008

본 논문에서는 8개의 문장에 대해서 6명의 화자가 5가지 감정 상태로 발화한 총 240개의 문장을 감정 음성 말뭉치로 활용하여 각 감정 상태에서 특징적으로 나타나는 억양 패턴을 분석하고, 이러한 억양 패턴을 음성 합성 시스템에 적용하는 방법에 대해서 논의한다. 이를 위해 본 논문에서는 감정 상태에 따른 특징적 억양 패턴을 억양구의 길이, 억양구의 구말 경계 성조, 하강 현상에 중점을 두어 분석하고, 기쁨, 슬픔, 화남, 공포의 감정을 구분 지을 수 있는 억양 특징들을 음성 합성 시스템에 적용하는 과정을 보인다. 본 연구를 통해 화남의 감정에서 나타나는 억양의 상승 현상을 확인할 수 있었고, 각 감정에 따른 특징적 억양 패턴을 찾을 수 있었다.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.939-941
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• 2021

사람은 표정, 음성, 말 등을 통해 감정을 표출한다. 본 논문에서는 화자의 음성데이터만을 사용하여 감정을 분류하는 방법을 제안한다. 멜 스펙트로그램(Mel-Spectrogram)을 이용하여 음성데이터를 시간에 따른 주파수 영역으로 변화한다. 멜 스펙트로그램으로 변환된 데이터를 CNN을 이용하여 특징 벡터화한 후 Bi-Directional LSTM을 이용하여 화자의 발화 시간 동안 변화되는 감정을 분석한다. 마지막으로 완전 연결 네트워크를 통해 전체 감정을 분류한다. 감정은 Anger, Excitement, Fear, Happiness, Sadness, Neutral로, 총 6가지로 분류하였으며 데이터베이스로는 상명대 연구팀에서 구축한 한국어 음성 감정 데이터베이스를 사용하였다. 실험 결과 논문에서 제안한 CNN-LSTM 모델의 정확도는 88.89%로 측정되었다.

• KIISE Transactions on Computing Practices
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• v.23 no.6
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• pp.386-391
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• 2017

In this paper, we propose a system that automatically assigns user's experience-based emotion tags from wearable sensor data collected in real life. Four types of emotional tags are defined considering the user's own emotions and the information which the user sees and listens to. Based on the collected wearable sensor data from multiple sensors, we have trained a machine learning-based tagging system that combines the known auxiliary tools from the existing affective computing research and assigns emotional tags. In order to show the usefulness of this multi-modality-based emotion tagging system, quantitative and qualitative comparison with the existing single-modality-based emotion recognition approach are performed.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2013.06a
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• pp.56-57
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• 2013

본 논문에서는 연극공연을 관람하는 관객의 반응정보를 수집하기 위하여, 청각센서를 통해 관객의 음성을 획득하고 획득된 음성에 대한 감정을 예측하여 관객 반응정보 관리시스템에 전송하는 음성신호 기반 감정인식 시스템을 구현한다. 이를 위해, 관객용 헤드셋 마이크와 다채널 녹음장치를 이용하여 관객음성을 획득하는 인터페이스와 음성신호의 특징벡터를 추출하여 SVM (support vector machine) 분류기에 의해 감정을 예측하는 시스템을 구현하고, 이를 관객 반응정보 수집 시스템에 적용한다. 실험결과, 구현된 시스템은 6가지 감정음성 데이터를 활용한 성능평가에서 62.5%의 인식률을 보였고, 실제 연극공연 환경에서 획득된 관객음성과 감정인식 결과를 관객 반응정보 수집 시스템에 전송함을 확인하였다.

• Journal of the Korean Society of Marine Environment & Safety
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• v.21 no.6
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• pp.721-728
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• 2015

Due to paradigm shift in administration, the field of police administration, like its civilian counterpart, is spending effort to improve customer-oriented civil complaint service system, and this is leading to a negative factor in service providers, emotional labor, among police officers. This study examines amount of emotional labor of maritime police officers, and verify the effects of emotional labor on exhaustion. Results show maritime police officers experience about the same amount of emotional labor as other public workers, and emotional labor has effects on work exhaustion. In other words, perception of incongruity of emotion has positive effects on exhaustion on cynical attitude. Attention to emotional expression has negative effects on decrease of job effectiveness. As such, if the problem of emotional labor is neglected, it leads to exhaustion and can become a significant obstacle to performance due to negative organizational influence. Also, it can lead to serious physical and mental problems on the individual level. Therefore, policy implementation to prevent this problem is necessary.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.547-552
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• 2008

Human and robot will have closer relation in the future, and we can expect that the interaction between human and robot will be more intense. To take the advantage of people's innate ability of communication, researchers concentrated on the facial expression so far. But for the robot to express emotional intensity, other modalities such as gesture, movement, sound, color are also needed. This paper suggests that the intensity of emotion can be expressed with color and blinking so that it is possible to apply the result to LED. Color and emotion definitely have relation, however, the previous results are difficult to implement due to the lack of quantitative data. In this paper, we determined color and blinking period to express the 6 basic emotions (anger, sadness, disgust, surprise, happiness, fear). It is implemented on avatar and the intensities of emotions are evaluated through survey. We figured out that the color and blinking helped to express the intensity of emotion for sadness, disgust, anger. For fear, happiness, surprise, the color and blinking didn't play an important role; however, we may improve them by adjusting the color or blinking.