• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.3
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• pp.337-342
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• 2010

The rise of music resources has led to a parallel rise in the need to manage thousands of songs on user devices. So users are tend to build play-list for manage songs. However the manual selection of songs for creating play-list is bothersome task. This paper proposes an auto play-list recommendation system considering user's context of use and preference. This system has two separate systems: mood and emotion classification system and music recommendation system. Users need to choose just one seed song for reflection their context of use and preference. The system recommends songs before the current song ends in order to fill up user play-list. User also can remove unsatisfied songs from recommended song list to adapt user preferences of the system for the next recommendation precess. The generated play-lists show well defined mood and emotion of music and provide songs that user preferences are reflected.

• 재활복지
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• v.20 no.1
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• pp.113-130
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• 2016

The purpose of this study is to determine the effects of guided imagery activities using music on both mood states and physiological responses of psychiatric inpatients. The experimental group was consisted of 27 psychiatric patients participating in the guided imagery activities using music for 11 minutes. Also, the control group was formed with 27 psychiatric patients with non-musical intervention. Mood states, blood pressure, pulse and skin temperature were checked before and after session. We could see the significant difference in the score of five areas-tension, depression, anger, vigor, fatigue-showed most differences in score. Also, the score of skin temperature of both experimental group and between two groups showed significant differences, too. Therefore, we can conclude that these results were showing that guided imagery activities using music was an effective nursing intervention method for altering mood state of psychiatric patients. Besides, it seemed to have physiological impact to make patients relax tension backed up by change of skin temperature.

• Journal of the Korea Convergence Society
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• v.10 no.9
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• pp.23-29
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• 2019

In this paper, the mood of images was classified into eight categories through a deep convolutional neural network and video was automatically generated using proper background music. Based on the collected image data, the classification model is learned using a multilayer perceptron (MLP). Using the MLP, a video is generated by using multi-class classification to predict image mood to be used for video generation, and by matching pre-classified music. As a result of 10-fold cross-validation and result of experiments on actual images, each 72.4% of accuracy and 64% of confusion matrix accuracy was achieved. In the case of misclassification, by classifying video into a similar mood, it was confirmed that the music from the video had no great mismatch with images.

• Journal of Korea Multimedia Society
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• v.10 no.3
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• pp.391-400
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• 2007

According to the recent advances in multimedia computing, storage and searching technology have made large volume of music contents become prevalent. Also there has been increasing needs for the study on efficient categorization and searching technique for music contents management. In this paper, a new classifying method using the local information of music content and music tone feature is proposed. While the conventional classifying algorithms are based on entire information of music content, the algorithm proposed in this paper focuses on only the specific local information, which can drastically reduce the computing time without losing classifying accuracy. In order to improve the classifying accuracy, it uses a new classification feature based on music tone. The proposed method has been implemented as a part of MuSE (Music Search/Classification Engine) which was installed on various systems including commercial PDAs and PCs.

• Journal of Korea Society of Industrial Information Systems
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• v.18 no.4
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• pp.25-35
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• 2013

This paper focuses on building a generalized mood classification model with many mood classes instead of a personalized one with few mood classes. Two methods are adopted to improve the performance of mood classification. The one of them is feature reduction based on standard deviation of feature values, which is designed to solve the problem of lowered performance when all 391 features provided by MIR toolbox used to extract features of music. The experiments show that the feature reduction methods suggested in this paper have better performance than that of the conventional dimension reduction methods, R-Square and PCA. As performance improvement by feature reduction only is subject to limit, modular neural network is used as another method to improve the performance. The experiments show that the method also improves performance effectively.

• Korean Journal of Biological Psychiatry
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• v.18 no.3
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• pp.134-140
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• 2011

Objectives Postpartum blues is known to be a major risk factor for postpartum depression and can be associated with the problems of language skills, behaviors or learning skills of their children. Therefore, it is very important for clinicians to evaluate precisely and control postpartum blues. Recent studies have found that music has an effect on depressive mood and the frontal EEG asymmetry of the patients with depression. The purpose of this study was to find out the effects of music on the frontal EEG asymmetry of the mothers with postpartum blues. Method Among one hundred and seventy mothers assessed with Korean version of the Edinburg Postnatal Depression Scale (EPDS), nine mothers with postpartum blues (EPDS ${\geq}$ 10) as postpartum blues group and nine non-depressive mothers (EPDS < 10) as non-depressive mother group were included. Ten non-labored, non-depressive women were also included as a normal control group. The subjects were evaluated with the State Trait Anxiety Inventory (STAI)-X1, the Visual Analogue Scale (VAS) and the Depression Adjective Checklist-Korean version (K-DACL) and EEG twice before and after the music sesssion with the length of twenty minutes and thirty two seconds. The statistical analyses were done for A1 score (log R - log L) which were computed from the alpha powers at F3 and F4. Results No significant difference was noted in demographic data among all three groups. The postpartum blues group had higher scores in the STAI-X1, the VAS and the K-DACL compared to the other groups at baseline, and their A1 scores were lower than those of only normal controls. There was a statistically significant increase of A1 score only in the postpartum blues group after the music session. Conclusion This study suggests that the mothers with postpartum blues may have a frontal EEG asymmetry which is possibly associated with their depressive mood, and the music session can affect the frontal asymmetry positively.

• Journal of Music and Human Behavior
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• v.15 no.1
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• pp.51-68
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• 2018

The purpose of this study was to examine the use of music by international college students in Korea. A questionnaire was administered to foreign college students. The questionnaire was composed of 25 items regarding use of music, the purpose of music use, and demographic information. A total of 150 questionnaires were distributed, and 81 questionnaires were returned. Incomplete questionnaires were excluded, and the remaining 69 questionnaires were analyzed. The results of this study were as follows. First, international students in Korea preferred listening to music over playing instruments or singing and mostly listened to popular music in their dormitory alone. They mostly listened to popular songs with love related themes and preferred music from their own country over Korean music. Second, in terms of the purpose behind music use, comfort was the reason reported most frequently, followed by mood change, enjoyment, sense of belonging, and sense of achievement. Third, there were no significant differences in use of music depending on individual factors (e.g., gender, length of residence in Korea, length of previous music education), but significant differences were found for using music for the purpose of mood change and sense of belonging based on respondents' length of residence in Korea. The results of this study may contribute to the development of musical programs for cultural adaptation and psycho-emotional support for international students in Korea.

• Journal of Families and Better Life
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• v.29 no.5
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• pp.153-163
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• 2011

This study was to investigate the effects of percussion program on depression and self-esteem for the elderly lived in residential care. 12 older adults participated in the 40-min. percussion program for 4 weeks(10 sessions). The percussion program consisted of three steps; 1) introduction for creating rapport and relationship, 2) process for mood induction and increasing interaction, and ending for increasing self-achievement and confirming the changed mood. Korean Geriatric Depression Scale (KGDS) and Self-Esteem Scale (SES) were administered before the first session and after the completion of the program. Results showed statistical significance (p<.05) in KGDS (p=.020) and SES (p=.025). Findings imply that percussion program can induce positive changes in depression and self-esteem for elderly in the residential care, and more depressed elderly group may have better outcome in percussion playing. Future studies should consider various levels of depression among elderly, and design the program to be more sensitive to the level of functioning.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.1
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• pp.19-24
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• 2010

The rise of music resources has led to a parallel rise in the need to manage thousands of songs on user devices. So users have a tendency to build playlist for manage songs. However the manual selection of songs for creating playlist is a troublesome work. This paper proposes an auto playlist generation system considering user context of use and preferences. This system has two separated systems; 1) the mood and emotion classification system and 2) the music recommendation system. Firstly, users need to choose just one seed song for reflecting their context of use. Then system recommends candidate song list before the current song ends in order to fill up user playlist. User also can remove unsatisfied songs from the recommended song list to adapt the user preference model on the system for the next song list. The generated playlists show well defined mood and emotion of music and provide songs that the preference of the current user is reflected.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.5
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• pp.80-86
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• 2010

This paper presents automated music story video generation technique as one of entertainment features that is equipped in multimedia system of the vehicle. The automated music story video generation is a system that automatically creates stories to accompany musics with photos stored in user's mobile phone by connecting user's mobile phone with multimedia systems in vehicles. Users watch the generated music story video at the same time. while they hear the music according to mood. The performance of the automated music story video generation is measured by accuracies of music classification, photo classification, and text-keyword extraction, and results of user's MOS-test.