• 한국HCI학회:학술대회논문집
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• 2006.02a
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• pp.400-405
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• 2006

In this paper, we present effective methods for music summarization which summarize music automatically. It could be used for sample music of on-line digital music provider or some music retrieval technology. When summarizing music, we use different two methods according to music length. First method is for finding sabi or chorus part of music which can be regarded as the most important part of music and the second method is for extracting several parts which are in different structure or have different mood in the music. Our proposed music summarization system is better than conventional system when structure of target music is explicit. The proposed method could generate just one important segment of music or several segments which have different mood in the music. Thus, this scheme will be effective for summarizing music in several applications such as online music streaming service and sample music for Tcommerce.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.8 no.4
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• pp.275-280
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• 2015

In this paper, we studied for modified MUSIC algorithm of direction of arrival (DOA)estimation. Modified MUSIC algorithm search optimal covariance matrix using singular value decomposition and Bayes method, and desired signals are estimated by updating weight. In order to estimation of desired signals, we used sub spatial method of MUSIC algorithm. General MUSIC algorithm can estimate a desired signal in case of non-correlation signal. But, general MUSIC algorithm in case of correlation signal can not estimate a desired signals and resolution is decreased. Though simulation in case of correlation signal, we analyze to compare proposed MUSIC algorithm with general MUSIC algorithm.

• The Journal of the Convergence on Culture Technology
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• v.9 no.4
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• pp.309-314
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• 2023

This study examines the development and limitations of current artificial intelligence (AI) music composition programs. AI music composition programs have progressed significantly owing to deep learning technology. However, they possess limitations pertaining to the creative aspects of music. In this study, we collect, compare, and analyze information on existing AI-based music composition programs and explore their technical orientation, musical concept, and drawbacks to delineate future directions for AI music composition programs. Furthermore, this study emphasizes the importance of developing AI music composition programs that create "personalized" music, aligning with the era of personalization. Ultimately, for AI-based composition programs, it is critical to extensively research how music, as an output, can touch the listeners and implement appropriate changes. By doing so, AI-based music composition programs are expected to form a new structure in and advance the music industry.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.4
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• pp.1869-1886
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• 2018

This paper proposes a MIDI- and audio-based music genre classification method for Korean traditional music. There are many traditional instruments in Korea, and most of the traditional songs played using the instruments have similar patterns and rhythms. Although music information processing such as music genre classification and audio melody extraction have been studied, most studies have focused on pop, jazz, rock, and other universal genres. There are few studies on Korean traditional music because of the lack of datasets. This paper analyzes raw audio and MIDI phrases in Korean traditional music, performed using Korean traditional musical instruments. The classified samples and MIDI, based on our classification system, will be used to construct a database or to implement our Kontakt-based instrument library. Thus, we can construct a management system for a Korean traditional music library using this classification system. Appropriate feature sets for raw audio and MIDI phrases are proposed and the classification results-based on machine learning algorithms such as support vector machine, multi-layer perception, decision tree, and random forest-are outlined in this paper.

• Smart Media Journal
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• v.10 no.4
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• pp.80-90
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• 2021

Using optical music recognition technology based on deep learning, we propose to apply the results derived to VR games. To detect the music objects in the music sheet, the deep learning model used YOLO v5, and Hough transform was employed to detect undetected objects, modifying the size of the staff. It analyzes and uses BPM, maximum number of combos, and musical notes in VR games using output result files, and prevents the backlog of notes through Object Pooling technology for resource management. In this paper, VR games can be produced with music elements derived from optical music recognition technology to expand the utilization of optical music recognition along with providing VR contents.

• The Korean Journal of Nuclear Medicine Technology
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• v.28 no.1
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• pp.31-33
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• 2024

Purpose: Music therapy helps alleviate anxiety, depression, and pain for cancer patients, contributing to stress relief. With such advantages, music therapy is applied across a broad spectrum of treatment areas, including mental disorders, developmental disabilities, and conditions affecting the elderly. It has been shown to enhance the quality of life for terminally ill cancer patients. Recent research has revealed its positive effects in boosting immune function and resilience. In light of these findings, the author conducted a study to investigate patient satisfaction with music listening. Materials and Methods: First, a survey was conducted with 30 individuals to inquire about the perceived necessity of listening to music in a waiting area. Next, participants were asked whether listening to music could contribute to psychological stability. Finally, preferences for music genres and satisfaction with music listening were assessed with a sample of 20 individuals. Results: In terms of the perceived necessity of listening to music in the waiting area, 28 out of 30 individuals, or 93%, expressed agreement. Regarding the belief that music listening could contribute to psychological stability, 28 out of 30 individuals, or 93%, believed that it would indeed help with stability. When it comes to preferred music genres, 4 individuals (13%) favored classical music, 2 individuals (6%) preferred traditional Korean music, 2 individuals (6%) enjoyed trot music, and 20 individuals (66%) had no specific genre preference. As for music listening satisfaction, 17 out of 20 individuals, or 85%, reported being satisfied. Conclusion: When patients visit the hospital, stress can increase due to concerns about their medical conditions. To address this, providing a variety of music genres at the hospital has been effective in reducing patient stress and promoting psychological stability.

• Journal of the Korean Society of Clothing and Textiles
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• v.28 no.910
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• pp.1231-1241
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• 2004

The purpose of this study was to investigate the musicians' body image and fashion styles portrayed in Korea and American music' video in aspects of body dimension such as sex, race, nature, and technology. The results were as follows. In aspects of sex, male musicians showed the blurring of gender appearance, while female musicians reflected sexuality which intensified the gender norms. In aspects of race, musicians pursued the racial blending appearances. In nature and technology dimension, Korea music video focused on natural imagery, while American music video showed a lot of technology imagies. And, the body combined with the nature and technology implied the post human image in the future.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1654-1659
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• 2003

In this paper, the performance evaluation of the JADE-MUSIC estimation based on the indoor channel is presented. By means of the JADE-MUSIC algorithm, DOA and time delay can be obtained simultaneously. In the JADE-MUSIC method, the channel impulse response is first estimated from the received samples and then this impulse response is employed to estimate DOAs and time delays of multipath waves. Moreover, according to the JADE-MUSIC characteristics, it can work in cases when the number of impinging waves is more than the number of antenna elements, unlike the traditional parametric subspace-based method, such a case is not true. Therefore, we employ the JADE-MUSIC algorithm applying for the real indoor environment where is rich of the multipath propagation waves and can imply that the number of waves is very possibly higher than that of the array element. The experiment is carried out in our laboratory considered to be the real indoor environment. The performance of the JADE-MUSIC algorithm is evaluated in terms of the comparison between the simulation and experiment results by using the simulated channel model and the real indoor channel model, respectively. It is clear that the joint angle and delay estimation using the simulated channel model are in good agreement with the estimation using the real indoor channel model. Therefore, we can say that the JADE-MUSIC algorithm accomplishes the high performance to jointly estimate the angle and delay of the arriving signal for the indoor environment.

• Journal of Koreanology Reviews
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• v.3 no.1
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• pp.7-13
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• 2024

The study aims to examine the development of the South Korean music industry over time in order to capture the evolution process of the industry from its initial stages to its current state as one of the world's leading music markets. Based on the above consideration, a systematic literature review was conducted in order to provide an overview of the achievements of the South Korean music industry with the help of PRISMA method. The reason for doing this is to ensure that the process of selecting, filtering and collecting literature from different sources is not only efficient and time-saving but also rigid and coherent. This paper will explore the various elements that have defined the industry, including culture, technology, marketing and government policies and regulations (Jang & Song, 2017). Furthermore, it will inquire the effects of the K-pop cultural export on other industries, whether it be tourism, fashion, consumer goods, and more, thereby illustrating its vast significance. In more detail, this study aims to give an adequate idea about the historical accomplishments of the South Korean music industry in the global music map, identify factors that facilitated the enhancement of the industry and examine the significance of the findings and their applications for the industry's progression and development in the future.

• Journal of Information Technology Applications and Management
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• v.23 no.1
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• pp.33-43
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• 2016

Along with the spread of digital music and recent growth in the digital music industry, the demands for music recommender are increasing. These days, listeners have increasingly preferred to digital real-time streamlining and downloading to listen to music because it is convenient and affordable for the listeners to do that. We use Bayesian learning through weight of listener's prefered music site such as Melon, Billboard, Bugs Music, Soribada, and Gini. We reflect most popular current songs across all genres and styles for music recommender system using user profile. It is necessary for us to make the task of preprocessing of clustering the preference with weight of listener's preferred music site with popular music charts. We evaluated the proposed system on the data set of music sites to measure its performance. We reported some of the experimental result, which is better performance than the previous system.