• Journal of IKEEE
• /
• v.21 no.4
• /
• pp.397-403
• /
• 2017

In the modern society, psychological diseases and impulsive crimes due to stress are occurring. In order to reduce the stress, the existing treatment methods consisted of continuous visit counseling to determine the psychological state and prescribe medication or psychotherapy. Although this face-to-face counseling method is effective, it takes much time to determine the state of the patient, and there is a problem of treatment efficiency that is difficult to be continuously managed depending on the individual situation. In this paper, we propose an artificial intelligence emotion management system that emotions of user monitor in real time and induced to a table state. The system measures multiple bio-signals based on the PPG and the GSR sensors, preprocesses the data into appropriate data types, and classifies four typical emotional states such as pleasure, relax, sadness, and horror through the SVM algorithm. We verify that the emotion of the user is guided to a stable state by providing a real-time emotion management service when the classification result is judged to be a negative state such as sadness or fear through experiments.

• Journal of Broadcast Engineering
• /
• v.25 no.5
• /
• pp.742-749
• /
• 2020

This paper proposes a method for recognizing both phoneme and emotion using a common neural network and a multi-task training method for the common neural network. The common neural network performs the same function for both recognition tasks, which corresponds to the structure of multi-information recognition of human using a single auditory system. The multi-task training conducts a feature modeling that is commonly applicable to multiple information and provides generalized training, which enables to improve the performance by reducing an overfitting occurred in the conventional individual training for each information. A method for increasing phoneme recognition performance is also proposed that applies weight to the phoneme in the multi-task training. When using the same feature vector and neural network, it is confirmed that the proposed common neural network with multi-task training provides higher performance than the individual one trained for each task.

• Journal of the Korea Convergence Society
• /
• v.10 no.9
• /
• pp.237-247
• /
• 2019

The purpose of this study was to evaluate the level and intensity of emotional labor of physical therapists and occupational therapists, and to identify the factors affecting them. Cross-sectional study was conducted on physical therapists and occupational therapists across the country using self-populated questionnaire. A total of 2,000 questionnaires were distributed to retrieve 1,500 questionnaires(75%), of which 1,374 questionnaires(68.7%) were finally analyzed, excluding 126 that answered duplicates or were missing answers. Multi-linear regression was performed to identify factors on the strength of emotional labor. According to the analysis results, high-risk groups in the areas under 'Emotional demand and regulation' and 'Overload and conflict in customer service' and 'Emotional disharmony and hurt' were 29.4%, 19.0% and 22.0% respectively, especially in 'Emotional demand and regulation', 'Overload and conflict in customer service', 'Emotional disharmony and hurt' for women working days, and 49% of daily work hours. Accordingly, we will be able to regularly screen physical therapists and occupational therapists for dangerous groups, and manage the intensity of emotional labor through the creation of a therapist's working environment, such as limiting overtime hours and assigning appropriate number of patients. Through this study, the grounds and methods for mitigating the negative effects of emotional labor and mediating emotional labor should be provided.

• Annual Conference on Human and Language Technology
• /
• 2011.10a
• /
• pp.37-41
• /
• 2011

본 논문에서는 최근 많은 관심을 받고 있는 Opinion Mining으로서 사용자들의 자연어 형태의 영화평 문장을 분석하여 자동으로 평점을 예측하는 시스템을 제안한다. 제안 시스템은 영화평 분석에 적합한 어휘 자질, 감정 자질, 가치 자질 및 기타 자질들을 추출하고, 10점 척도의 영화평의 평점을 10개의 범주로 가정하여, 커널모델인 다중 범주 Support Vector Machine (SVM) 모델을 이용하여 높은 성능으로 영화평의 평점을 범주 분류한다.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2002.04b
• /
• pp.817-820
• /
• 2002

인간과 기계와의 인터페이스에 있어서 궁극적 목표는, 인간과 기계가 마치 사람과 사람이 대화하듯 자연스런 인터페이스가 이루어지도록 하는데 있다. 이에 본 논문에서는 사람의 음성속에 깃든 6개의 기본 감정을 인식하는 알고리듬을 제안하고자 한다. 이를 위하여 뛰어난 주파수 분해능력을 갖고 있는 웨이블렛 필터뱅크를 이용하여 음성을 여러 개의 서브밴드로 나누고 각 밴드에서 특징점을 추출하여 감정을 이식하고 이를 최종적으로 융합, 단일의 인식값을 내는 다중의사 결정 구조를 갖는 알고리듬을 제안하였다. 이를 적용하여 실제 음성 데이타에 적용한 결과 기존의 방법보다 높은 90%이상의 인식률을 얻을 수 있었다.

• Journal of Digital Contents Society
• /
• v.19 no.4
• /
• pp.821-827
• /
• 2018

Affective computing has gained increasing interest in the recent years with the development of potential applications in Human computer interaction (HCI) and healthcare. Although momentous research has been done on human emotion recognition, however, in comparison to speech and facial expression less attention has been paid to physiological signals. In this paper, Electroencephalogram (EEG) signals from different brain regions were investigated using modified wavelet energy features. For minimization of redundancy and maximization of relevancy among features, mRMR algorithm was deployed significantly. EEG recordings of a publically available "DEAP" database have been used to classify four classes of emotions with Multi class Support Vector Machine. The proposed approach shows significant performance compared to existing algorithms.

• Journal of Internet of Things and Convergence
• /
• v.7 no.2
• /
• pp.31-40
• /
• 2021

Objectives: This study was conducted to investigate the degree of verbal abuse, emotional response, nursing professionalism, clinical practice stress during clinical practicim of nursing students. Methods: A sample of convenience was 106 nursing students, and a questionnaire was used to measure their verbal abuse, emotional response, nursing professionalism, clinical practice stress. Data were analyzed by descriptive statistics, t-test, one-way ANOVA, and multiple linear regression. Results: A significant positive correlation was found among verbal abuse, emotional response, clinical practice stress(r=.683, r=.573). Grade of which the participant was in, verbal abuse(𝛽=.487), emotional response(𝛽=.240) were significant predictive variables of which accounted for 49% of the variance in clinical practice stress. Conclusions: The results from this study can provide basic data on the development of strategies for nursing college students to cope with verbal abuse and to manage stress under clinical practice

• Journal of Industrial Convergence
• /
• v.20 no.12
• /
• pp.269-276
• /
• 2022

This study was conducted with the purpose of verifying the effect of the working environment of elderly care workers on service quality and the mediating effect of emotional labor and recognition of filial piety. The subjects of the study were 460 elderly care workers. For the collected data, SPSS Process macro was used. As a result, First, it was found that all variables had a significant positive (+) relationship. Second, the parallel mediating effect of emotional labor and recognition of filial piety was confirmed. Third, the mediating effect of recognition of filial piety and the moderating effect of emotional labor were verified. Based on this study, it was found that filial piety awareness education and emotional labor management are necessary. A follow-up study with a more expanded concept should be conducted.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.26 no.12
• /
• pp.1759-1768
• /
• 2022

This paper proposes a model to detect depression-related emotions in a user's speech using wellness dialogue scripts provided by AI Hub, topic-specific daily conversation datasets, and chatbot datasets published on Github. There are 18 emotions, including depression and lethargy, in depression-related emotions, and emotion classification tasks are performed using KoBERT and KOELECTRA models that show high performance in language models. For model-specific performance comparisons, we build diverse datasets and compare classification results while adjusting batch sizes and learning rates for models that perform well. Furthermore, a person performs a multi-classification task by selecting all labels whose output values are higher than a specific threshold as the correct answer, in order to reflect feeling multiple emotions at the same time. The model with the best performance derived through this process is called the Depression model, and the model is then used to classify depression-related emotions for user utterances.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.20 no.4
• /
• pp.177-188
• /
• 2019

Emotional labor is the process of regulating feelings or emotions and expressing them in the way that fulfill job requirement. There have been many studies about characteristics or related variables of service workers' emotional labor, but are few studies comparing emotional labor between service workers and non-service workers. Therefore we are to examine the differences of emotional labor among the different types of workers. And as depression and lowered quality of life are well known negative consequences of emotional labor, we also intend to study the relationship between depression, quality of life, and emotional labor. Data were collected from 125 sales workers, and 186 cyber university full time students. And as to assure the student participants to be non-service workers, we limited the participant job as administrator, soldier or housewife. To compare differences of groups, one-way ANOVA was performed with Fisher's LSD as post hoc comparison. On overload in customer reception, service workers showed significantly higher scores, and on demand of emotional regulation/emotional dissonance/depression, both service workers and housewives showed significantly higher scores. Also analysis of multiple regression was performed, and the result showed that, emotional dissonance increased depression but decreased quality of life, while support/care increased quality of life, but decreased depression. With the result, implications and limitations of this study were discussed.