• 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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.7
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• pp.869-876
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• 2021

In the field of music, various AI composition methods using machine learning have recently been attempted. However, most of this research has been centered on Western music, and little research has been done on Korean traditional music. Therefore, in this paper, we will create a data set of Korean traditional music, create a melody using three algorithms based on the data set, and compare the results. Three models were selected based on the similarity between language and music, LSTM, Music Transformer and Self Attention. Using each of the three models, a melody generator was modeled and trained to generate melodies. As a result of user evaluation, the Self Attention method showed higher preference than the other methods. Data set is very important in AI composition. For this, a Korean traditional music data set was created, and AI composition was attempted with various algorithms, and this is expected to be helpful in future research on AI composition for Korean traditional music.

• Korean Journal of Human Ecology
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• v.24 no.1
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• pp.79-96
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• 2015

The purpose of this research was to analyze the clothing behavioral attributes of male music enthusiasts. A questionnaire was developed based on previous researches. Respondents were men who were concerned with music in terms of a job, a major or a hobby. A total of 200 responses were analyzed by SPSS 20.0 through factor analysis with Varimax rotation, ANOVA with post-hoc test(SNK-test) and ${\chi}^2$-test. Music preference was classified into 3 factors: New age/jazz, Hiphop/dance, and Metal rock/ballad factor. 5 Clothing purchasing orientation factors were extruded: hedonic, planned, convenience, brand pursued, and fashion pursued purchasing orientation. Using those factor scores, 3 groups were classified: Group1(G1), preferring Hiphop/dance music with lower hedonic and brand/fashion pursued purchasing orientation; G2, preferring Hiphop/dance music with no interest in clothing shopping and fashion; G3, preferring New age music with high convenience and brand pursued purchasing orientation. In addition, there were significant differences among groups in clothing behavior such as social ostentation, individuality, self-expression, fashionability, conformity; in purchase motivation such as hedonic and trend/designer oriented purchase motivation; in information source like advertisement/media source; and in store choice criteria such as store light/music and popularity. The findings showed even the enthusiasts for the same music showed the different sopping orientation and different clothing behavior, suggesting that a personal value or taste can be a plausible factor to figure out attributes of consumers. An interest/involvement in clothing could be helpful to subdivide the music enthusiasts as the target market.

• Journal of Korea Entertainment Industry Association
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• v.15 no.4
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• pp.101-111
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• 2021

This paper is a study that analyzes the use and techniques of rap in music that entered Melon Chart, one of the major music sites in Korea, during 2020. Among the songs that entered the chart, reflecting the public's preference, the trend of rap music, an important element of hip-hop music, is analyzed and musical features such as representative artists or frequently used rhythm patterns are analyzed. Through this paper, characteristics of rap music favored by the public and artists in recent popular music have been organized and formalized, and based on this, the elements of etude development for technical polishing are summarized. Through this, it is hoped that just like the long-time analyzed and structured performance techniques such as vocals and instruments, various styles of rap music can develop into a systematic and step-by-step technique system for students who want to learn and practice it.

• Fashion & Textile Research Journal
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• v.5 no.5
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• pp.465-469
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• 2003

The present study revealed; that (1) The students majoring in a piano course were the preference type of the performance dress - best line was designed of upper form chest. It was 1.5cm shorter than armhole line, the princess line was preferred Top one piece without sleeves which was designed with slim by bottom line through west dart form best line. The expression method was showing embroidery and bidding, colors were in order to white, ivory, black and blue style. The material was in order to silk with glorious shinning, silk satin and race style. (2) The students majoring in a vocal music were the preference type of the performance dress - the princess line was designed shorter, the west line of back and forth was preferred the one piece of bulk style divided with three partitions. Neck line was 5cm shorter than the middle of back, 9cm shorter than the side neck position, 9cm shorter than the middle of forth, sweet heart neck line with circular sleeve designed 7cm shorter than the side neck position. Colors were in order to ivory, red and yellow style. The material was in order to silk with glorious shinning silk satin and race style.

• KIEAE Journal
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• v.12 no.4
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• pp.83-88
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• 2012

As for the generally preferred sound sources used in the test, the sound of water and the birds chirping were highly valued. And they have found that preference of the subject is increased if background music which mixed well with the sound sources were provided together. On the other hand, the sound sources of low satisfaction were judged at be church bells, bell of Emile, and fulling cloth, which not mix well with interior landscaping. If the physical elements of interior landscaping were equally composed, it has found that the larger were a of water space is, the higher satisfaction more than other sound sources. Average satisfaction of background sound in interior landscaping classified according to the characteristics of space has found that satisfaction of the birds chirping and music in working space and satisfaction of water sound and music in commercial space were high. Women judged that satisfaction of the birds chirping and music in working space and satisfaction of water sound and music in commercial space whose values were the same with the average ones were high, while men judged that satisfaction of the song of birds and music in working and commercial space is high.

• Journal of Digital Contents Society
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• v.8 no.4
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• pp.521-529
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• 2007

In this paper, we introduce a music recommendation system that automatically recommends music according to users' musical tastes. The recommendation system uses a graph-based collaborating filtering in which similarities between musics are saved as a graph, and so it can perform fast recommendation based on the implicit preference information. It also has capability of recommending music according to users' dynamically changing preferences as well as users' static preferences. The recommendation server is implemented as an independent server using Java, and communicates with clients according to a specified protocol. A demo web site has been built by using the server and music download data from actual users, and the accuracy of recommendation has been measured through experiments.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.10
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• pp.399-406
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• 2021

With the steady growth of the content industry, the need for research that automatically recommending content suitable for individual tastes is increasing. In order to improve the accuracy of automatic content recommendation, it is needed to fuse existing recommendation techniques using users' preference history for contents along with recommendation techniques using content metadata or features extracted from the content itself. In this work, we propose a new graph-based music recommendation method which learns an LSTM-based classification model to automatically extract appropriate tagging words from sound data and apply the extracted tagging words together with the users' preferred music lists and music metadata to graph-based music recommendation. Experimental results show that the proposed method outperforms existing recommendation methods in terms of the recommendation accuracy.

• The Journal of the Acoustical Society of Korea
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• v.25 no.4
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• pp.191-196
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• 2006

Human tend to rely their information about the size of a space on vision. However, it might be a common experience to perceive a certain difference in spaces without any visual difference, in such spaces as rooms for music performance, multimedia environments with multiple sound sources, and car cabins, where auditory experiences have a certain importance. In the present work, apparent auditory room size was measured at different positions in a room through a series of listening experiments. Also, measurement of room acoustic parameters was carried out and their relationships with perceived auditory room size were analyzed. The results suggest that apparent auditory room sizes were largely dependent on musical clarity, distance between a source and a receiver, and sound pressure level at the listening position. Also, the results from acoustic preference test suggest that smaller apparent room sizes were preferred for listening to orchestral, cello and flute music. The relationship between apparent auditory room size and vocal music was found to be statistically insignificant.

• Fashion & Textile Research Journal
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• v.17 no.4
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• pp.524-540
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• 2015

This study develops textile pattern design ideas created through the visualization of music. Methods of auditory and synesthesia were employed to analyze various attributes of popular music genres and appoint language image, shape image, and color image to obtain their interrelationships. This study provides data that can be used to express emotional images on textile print pattern designs. This research used different genres of popular music as stimuli. The language image was extracted and introduced to the overall color scheme; in addition, the color image was verified. The analysis of the color image was executed by applying it with the color set image scale of I.R.I colors. Then, the color image of the target genre of popular music was examined and analyzed through a color tone system. The preference in shape image was realized through visual images based on basic principles of points, lines, and sides composition; subsequently, an analysis of the emotional image of popular music followed. An examination of the emotional images of different popular music genres have led to the discovery that language image, color image, and shape image all share a common emotional image. There was also a realization that similarity and interrelationship exists in language, color, and shape images experienced by listening to popular music.