• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.4
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• pp.1464-1485
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• 2021

Emotional style of multimedia art works are abstract content information. This study aims to explore emotional style transfer method and find the possible way of matching music with appropriate images in respect to emotional style. DCNNs (Deep Convolutional Neural Networks) can capture style and provide emotional style transfer iterative solution for affective image generation. Here, we learn the image emotion features via DCNNs and map the affective style on the other images. We set image emotion feature as the style target in this style transfer problem, and held experiments to handle affective image generation of eight emotion categories, including dignified, dreaming, sad, vigorous, soothing, exciting, joyous, and graceful. A user study was conducted to test the synesthesia emotional image style transfer result with ground truth user perception triggered by the music-image pairs' stimuli. The transferred affective image result for music-image emotional synesthesia perception was proved effective according to user study result.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.11
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• pp.1598-1603
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• 2013

Recently, researches on analyzing relationship between the state of emotion and musical stimuli are increasing. In many previous works, data sets from all extracted channels are used for pattern classification. But these methods have problems in computational complexity and inaccuracy. This paper proposes a selection of optimal EEG channel to reflect the state of emotion efficiently according to music listening by analyzing stochastic feature vectors. This makes EEG pattern classification relatively simple by reducing the number of dataset to process.

• Korean Journal of Adult Nursing
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• v.13 no.4
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• pp.591-600
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• 2001

Purpose: This study was to observe the effects of music therapy on the cognitive function, behavior, and emotions of elderly dementia patients, and to seek musical mediation for them. This study was conducted with patients in the Dementia Sanitarium in C City from March 13 to April 17. Method: The design of research was a nonequivalent control group non-synchronized design and the subjects were 25 patients-15 of whom were in the experimental group with 10 in the control group. The music therapy consisted of favorite music listening in the morning, favorite music group singing activity after lunch, and relaxing music listening after dinner. The schedule was followed 6 days a week for 2 weeks for a total of thirty-six session. The effect of music therapy was measured by MMSE-K and the behavior and emotion measuring equipment which had been derived by the researcher. The verification of the effects is that the score of cognitive function, behavior, and emotions of the experimental and the control group which were measured after the therapy had been applied was analyzed by descriptive statistics and t - test using SPSS WIN program. Result: 1) The degree of cognitive function of the experimental group which was received the music therapy is $11.53{\pm}5.37$ which is a little higher than the control group which is $11.20{\pm}6.32$, but it is not significant statistically (t= .14, p= .887). The first hypothesis which had assumed the recepients would have had a higher cognitive function level than the other was rejected. 2) Behavior score of the experimental group that received the music therapy is $68.90{\pm}7.86$ which is higher than the control group which is $66.40{\pm}11.13$, but it is not significant statistically(t= .61, p= .548). The second hypothesis which had assumed the recepients would have had a higher behavior level than the other was rejected. 3) Emotions score of the experimental group that received the music therapy is $42.13{\pm}5.04$ which is higher than the control group which is $35.20{\pm}6.12$, and it is significant statistically(t=3..09, p= .009). The third hypothesis which assumed the recepients would have had a higher emotion level was supported. Conclusion: music therapy which is composed of listening to music and group singing activity is an effective strategy for improvement of the emotions of the dementia elderly. But, the effect of music therapy on the cognitive function and behavior of elderly dementia patients is not significant statistically.

• Journal of Information Processing Systems
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• v.13 no.2
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• pp.400-416
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• 2017

Music emotion is an important component in the field of music information retrieval and computational musicology. This paper proposes an approach for automatic emotion classification, based on rough set (RS) theory. In the proposed approach, four different sets of music features are extracted, representing dynamics, rhythm, spectral, and harmony. From the features, five different statistical parameters are considered as attributes, including up to the $4^{th}$ order central moments of each feature, and covariance components of mutual ones. The large number of attributes is controlled by RS-based approach, in which superfluous features are removed, to obtain indispensable ones. In addition, RS-based approach makes it possible to visualize which attributes play a significant role in the generated rules, and also determine the strength of each rule for classification. The experiments have been performed to find out which audio features and which of the different statistical parameters derived from them are important for emotion classification. Also, the resulting indispensable attributes and the usefulness of covariance components have been discussed. The overall classification accuracy with all statistical parameters has recorded comparatively better than currently existing methods on a pair of datasets.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.5
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• pp.637-644
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• 2011

Being digitalized, the music can be easily purchased and delivered to the users. However, there is still some difficulty to find the music which fits to someone's taste using traditional music information search based on musician, genre, tittle, album title and so on. In order to reduce the difficulty, the contents-based or the emotion-based music retrieval has been proposed and developed. In this paper, we propose new method to determine the importance of MPEG-7 low-level audio descriptors which are multi-dimensional vectors for the emotion-based music retrieval. We measured the mutual similarities of musics which represent a pair of emotions expressed by opposite meaning in terms of each multi-dimensional descriptor. Then rough approximation, and inter- and intra similarity ratio from the similarity relation are used for determining the importance of a descriptor, respectively. The set of weights based on the importance decides the aggregated similarity measure, by which emotion-based music retrieval can be achieved. The proposed method shows better result than previous method in terms of the average number of satisfactory musics in the experiment emotion-based retrieval based on content-based search.

• The Journal of the Acoustical Society of Korea
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• v.41 no.2
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• pp.115-121
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• 2022

In this paper, we propose a music classification system according to user emotions using Electroencephalogram (EEG) features that appear when listening to music. In the proposed system, the relationship between the emotional EEG features extracted from EEG signals and the auditory features extracted from music signals is learned through a deep regression neural network. The proposed system based on the regression model automatically generates EEG features mapped to the auditory characteristics of the input music, and automatically classifies music by applying these features to an attention-based deep neural network. The experimental results suggest the music classification accuracy of the proposed automatic music classification framework.

• The KIPS Transactions:PartB
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• v.17B no.2
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• pp.99-106
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• 2010

In this paper, we propose the construction of multi-queries and consistency principle for the user's emotion-based music retrieval system. The features used in the system are MPEG-7 audio descriptors, which are international standards recommended for content-based audio retrievals. In addition we propose the method to determine the weight that represent the importance of each descriptor for each emotion in order to reduce the computation. Also, the proposed retrieval algorithm that uses the relevance feedback based on consistency principal and multi-queries improves the success ratio of musics corresponding to user's emotion.

• International journal of advanced smart convergence
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• v.6 no.2
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• pp.9-15
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• 2017

According to a recent survey, most elementary and secondary school students nationwide are stressed out by their academic records. Furthermore most of high school students in Korea have to study under the great duress. Some of them who can't overcome the academic stress finalize their life by suiciding. A study has found that it is one of the leading causes of stimulating the thought of committing suicide in Korean high school students. So it is necessary to reduce the high school student's suicide rate. Main content of this research is to implement a personalized music recommendation system. Music therapy can help the student deal with the stress, anxiety and depression problems. Proposed system works as a therapist. The music choice and duration of the music is adjusted based on the student's current emotion recognized automatically from EEG. If the happy emotion is not induced by the current music, the system would automatically switch to another one until he or she feel happy. Proposed system is personalized brain music treatment that is making a brain training application running on smart phone or pad. That overcomes the critical problems of time and space constraints of existing brain training program. By using this brain training program, student can manage the stress easily without the help of expert.

• Journal of Sasang Constitutional Medicine
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• v.18 no.1
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• pp.30-40
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• 2006

1. Objectives The present study purposed to examine the contents and the principles of music therapy according to Oriental medicine theories in order to prove that music therapy is not a new research area but its principle is found in the long tradition of Oriental medicine. 2. Methods We investigate the possibility of music therapy based on Oriental medicine theories and examine the meanings of music therapy from the viewpoint of Oriental medicine. 3. Conclusions and discussions (1) The principles of music therapy are the principle of homogeneity, catharsis and balance. (2) When one’s mind changes, there are naturally occurred sounds, which are called Oseong (五聲: the oriental five voices exhalation, laughing, singing, wailing and groaning), and the notes defined by arranging the Oseong according to the principle of Ohaeng (五行: the oriental five phases wood, fire, earth, metal, water) are Oheum (五音: the oriental five musical notes Gakeum, Chieum, Gungeum, Sangeum and Wooeum.). If Eum (musical notes) is classified into Ohaeng, it can be divided into Gakeum, Chieum, Gungeum, Sangeum and Wooeum. (3) Change of Sinji (神志: consciousness) induces change of Gigi (氣機: function of Gi), which can change the character of voices. Oseong controls the functions of Ojang (五臟: the oriental five viscera) by ruling one’s Jeongji (情志: emotion). It can reduce the damage of the viscera caused by excessive vent of emotion resulted from unconscious expression of Oseong - Hoseong (呼聲: exhalation), Soseong (笑聲: laughing), Gaseong (歌聲: singing), Gokseong (哭聲: wailing) and Sinseong (呻聲: groaning). (4) Yijeongseungjeong (以情勝情: Control emotion with emotion) therapies, which suppresses an emotion by stimulating another, include Noseungsabeop (怒勝思法: Control anxiety with anger), Heeseungbibeop (喜勝悲法: Control sorrow with joyfulness), (思勝恐法: Control fear with anxiety), Biseungnobeop (悲勝愁法: Control anger with sorrow) and Gongseungheebeop (恐勝喜法: Control joyfulness with fear). (5) Seongeum (聲音: voices and musical notes) can be applied to a stimulation method that not only harmonizes the rhythm of living organs but also controls the occurrence of diseases caused by mutual Pyeonseongpyeonsoi (偏盛偏衰: relative preponderance and weakness) through direct induction of the strength and weakness of Gi function of the oriental five viscera in a human body according to the individual character. Sounds preferred by the patient, the material of an instrument selected by the patient, the character of rhythm and music expressed by the patient and the sound or voice uttered frequently by the patient can be considered in diagnosis and treatments for the patient’s body and mind.

• Journal of Korea Entertainment Industry Association
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• v.13 no.4
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• pp.17-26
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• 2019

In order to study the role of legato to singers in vocal music performance, this paper adopts the methods of demonstration and induction and comparison to analyze the three factors affecting the creation of legato in performance and propose solutions. When thinking about the influence of singing skills on legato, singers will be able to solve such issues as breathing, articulation and vocal register, thus improving their singing skills. When thinking about the influence of singing language on legato, singers will make an in-depth study on the phonetic and structural features of the language to reach legato in language, thus promoting the in-depth study of singers on the singing language. When thinking about the influence of singing emotion on legato, singers will solve the problem of emotional coherence from two aspects of thought and emotion to create legato of emotion, thus promoting the expression of singers' emotion in the work. Obviously, legato plays an important role in improving singers' singing skills, singing language and singing emotion. The aim of the paper is to encourage singers to further deepen their attention to legato in vocal music performance and make better use of legato in singing.