• International Journal of Fuzzy Logic and Intelligent Systems
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• v.11 no.2
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• pp.124-128
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• 2011

Music emotion recognition is currently one of the most attractive research areas in music information retrieval. In order to use emotion as clues when searching for a particular music, several music based emotion recognizing systems are fundamentally utilized. In order to maximize user satisfaction, the recognition accuracy is very important. In this paper, we develop a new music emotion recognition system, which employs a multilabel feature selector and multilabel classifier. The performance of the proposed system is demonstrated using novel musical emotion data.

• Journal of Korea Multimedia Society
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• v.25 no.2
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• pp.215-220
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• 2022

Emotion recognition is one of the most important and challenging areas of computer vision. Nowadays, many studies on emotion recognition were conducted and the performance of models is also improving. but, more research is needed on emotion recognition and sentiment analysis of video viewers. In this paper, we propose an emotion analysis system the includes a sentiment analysis model and an interest prediction model. We analyzed the emotional patterns of people watching popular and unpopular videos and predicted the level of interest using the emotion analysis system. Experimental results showed that certain emotions were strongly related to the popularity of videos and the interest prediction model had high accuracy in predicting the level of interest.

• Journal of Multimedia Information System
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• v.1 no.1
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• pp.55-67
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• 2014

Image topic and emotion analysis is an important component of online image retrieval, which nowadays has become very popular in the widely growing social media community. However, due to the gaps between images and texts, there is very limited work in literature to detect one image's Topics and Emotions in a unified framework, although topics and emotions are two levels of semantics that often work together to comprehensively describe one image. In this work, a unified model, Joint Topic/Emotion Multi-Modal Hierarchical Latent Dirichlet Allocation (JTE-MMHLDA) model, which extends previous LDA, mmLDA, and JST model to capture topic and emotion information at the same time from heterogeneous data, is proposed. Specifically, a two level graphical structured model is built to realize sharing topics and emotions among the whole document collection. The experimental results on a Flickr dataset indicate that the proposed model efficiently discovers images' topics and emotions, and significantly outperform the text-only system by 4.4%, vision-only system by 18.1% in topic detection, and outperforms the text-only system by 7.1%, vision-only system by 39.7% in emotion detection.

• Journal of the Ergonomics Society of Korea
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• v.22 no.3
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• pp.1-11
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• 2003

The objective of this research is the development of the Automatic Subjective Assessment System (ASAS). The proposed subjective assessment system is designed to evaluate human emotion and sensibility (or "gamsung" in Korean terminology) with subjective responses of volunteers about the experiment of emotion and sensibility. Once volunteers enter their subjective responses about the experiment into the developed system, the proposed system can automatically generate statistical results of human emotion and sensibility using Statistical Package for the Social Sciences (SPSS). Then, the system stores the statistical results in the database which will be open to public through internet. The proposed system will be integrated into the universal" gamsung" assessment system for evaluation of human emotion and sensibility.

• Journal of the Korea Convergence Society
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• v.8 no.7
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• pp.323-330
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• 2017

Emotion in early childhood has been observed to make an important effect on behavioral development. The teacher has coached to develop good behavior based on considering emotional response rather than rational response. This study was to determine significance of emotional coaching for behavior development according emotion recognized by non-verbal measurement system developed specially in this study. The participants were 44 people and were asked to study in four experimental situation. The experiment was designed to four situation such as class without coaching, behavioral coaching, emotion coaching, and emotion coaching based on emotional recognition system. The dependent variables were subjective evaluation, behavioral amplitude, and HRC (Heart Rhythm Coherence) of heart response. The results showed the highest positive evaluation, behavioral amplitude, and HRC at emotion coaching based on emotional recognition system. In post-doc analysis, the subjective evaluation showed no difference between emotion coaching and system based emotion coaching. However, the behavioral amplitude and HRC showed a significant response between two coaching situation. In conclusion, quantitative data such as behavioral amplitude and HRC was expected to solve the ambiguity of subjective evaluation. The emotion coaching of teacher using emotional recognition system was can be to improve positive emotion and psychological stability for children.

• Journal of Digital Convergence
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• v.17 no.1
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• pp.239-247
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• 2019

An accurate prediction of emotion is a very important issue for the sake of patient-centered medical device development and emotion-related psychology fields. Although there have been many studies on emotion prediction, no studies have applied the heart rate variability and neuro-fuzzy approach to emotion prediction. We propose ANFEP(Adaptive Neuro Fuzzy System for Emotion Prediction) HRV. The ANFEP bases its core functions on an ANFIS(Adaptive Neuro-Fuzzy Inference System) which integrates neural networks with fuzzy systems as a vehicle for training predictive models. To prove the proposed model, 50 participants were invited to join the experiment and Heart rate variability was obtained and used to input the ANFEP model. The ANFEP model with STDRR and RMSSD as inputs and two membership functions per input variable showed the best results. The result out of applying the ANFEP to the HRV metrics proved to be significantly robust when compared with benchmarking methods like linear regression, support vector regression, neural network, and random forest. The results show that reliable prediction of emotion is possible with less input and it is necessary to develop a more accurate and reliable emotion recognition system.

• Journal of the Ergonomics Society of Korea
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• v.31 no.6
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• pp.757-764
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• 2012

Objective: The aim of this study is to find the optimal values of sliding factors which influence the mechanical emotion of users when they use sliding type mobile phones. Background: There are various researches that study the emotion of using mobile phones. They focus the correlation between emotion words and design factors and use the commercial products by the subjects in the experiment. However, it has a limit in finding the optimal point of emotional factors because we can search the restricted values in the mass production of the products. Therefore, we will find the optimal points by realizing the full range of the user's mechanical emotion. Method: First, we need to get the detailed factors which can describe the mechanical emotion in sliding up and down the mobile phone. Next, we find the control factors by considering the correlation between the factors of the sliding emotion and the possibility of quantitative design. To find the optimal points on the control factors, we make a sliding evaluation system which can help users feel the sliding mechanical emotion by realizing control factors. Finally, we find the optimal points by doing the experiment the system being used. Results: The critical values of the factors which are the main variables of this study are Open Max Force and Dead point Ratio. The optimal point of the Open Max Force is 200~250g/f, and the Dead point Ratio is 40~50%. Conclusion: In this study we develop the sliding evaluation system to realize the control factors of the sliding type phone and find the optimal values of the critical factors. Application: The results can be used as the criteria for designing sliding type phone.

• Science of Emotion and Sensibility
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• v.10 no.1
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• pp.1-11
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• 2007

An Infotainment Service intended to enhance the human emotion is introduced in this paper. The service is to be installed on the robot helping elderly persons to live comfortable and enjoyable life. The research started with defining the undesirable status of emotion in everyday life, and the psychological skills to cope with the status were sought about. Then, a methodology for providing emotion contents reflecting the coping skill has been suggested. Based on the Cognitive Behavior Therapy, the coping skill is used to edit animation clips. A movie recommendation system to utilize the edited animation clips has been being developed. A series of process for developing the system is described, where the emotion elements are taken into consideration in addition to the user preference as the criterion for recommendation.

• The Journal of Korea Robotics Society
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• v.3 no.2
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• pp.154-163
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• 2008

This paper presents the concept for the development of a pet-type robot with an emotion engine. The pet-type robot named KOBIE (KOala roBot with Intelligent Emotion) is able to interact with a person through touch. KOBIE is equipped with tactile sensors on the body for interaction with a person through recognition of his/her touching behaviors such as "Stroke","Tickle","Hit". We have covered KOBIE with synthetic fur fabric in order to can make him/her feel affection as well. KOBIE is able to also express an emotional status that varies according to the circumstances under which it is presented. The emotion engine of KOBIE's emotion expression system generates an emotional status in an emotion vector space which is associated with a predefined needs and mood models. In order to examine the feasibility of our emotion expression system, we verified a changing emotional status in our emotion vector space by a touching behavior. We specially examined the reaction of children who have interacted with three kind of pet-type robots: KOBIE, PARO, AIBO for roughly 10 minutes to investigate the children's preference for pet-type robots.

• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.377-380
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• 2002

In this paper, speaker and context independent emotion recognition using speech signal is studied. For this purpose, a corpus of emotional speech data recorded and classified according to the emotion using the subjective evaluation were used to make statical feature vectors such as average, standard deviation and maximum value of pitch and energy and to evaluate the performance of the conventional pattern matching algorithms. The vector quantization based emotion recognition system is proposed for speaker and context independent emotion recognition. Experimental results showed that vector quantization based emotion recognizer using MFCC parameters showed better performance than that using the Pitch and energy Parameters.