• Korean Journal of Child Studies
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• v.28 no.1
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• pp.37-54
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• 2007

The purpose of this study was the development and validation of a test of young children's understanding and their ability to represent the elements of traditional Korean music. The test was reviewed by professional groups and modified by preliminary testing. In its final form, the Korean Traditional Music Ability Test(KTMAT) for 4- to 6-year-old children consists of 43 items covering understanding and ability to represent Changdan(Changdanhyung, Bak, Bbareugi and Semyeorim) and Garak(Eumjeong and Sikimshae). Item analysis, reliability and validity tests were statistically significant. The KTMAT is an evaluation tool that can be used as basic material for developing children's musical ability, and it can provide valuable information showing direction for children's Korean traditional music education.

• Proceedings of the Korea Contents Association Conference
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• 2004.11a
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• pp.308-313
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• 2004

In this paper, we compared and analyzed the discrimination performance of speech/music about combinations of each features parameter. Audio signals are classified into 3 classes (speech, music, speech and music). On three types of features, Mel-cepstrum, energy, zero-crossings used to the experiments. Then compared and analyzed the best of the combinations between features to speech/ music discrimination performance. The best result is achieved using Mel-cepstrum, energy and zero-crossings in a single feature vector (speech: 95.1%, music: 61.9%, speech & music: 55.5%).

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.146-149
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• 2014

In this paper, humming based automatic music creation method is described. It is difficult for the general public which does not have music theory to compose the music in general. However, almost people can make the main melody by a humming. With this motivation, a melody and chord sequences are estimated by the humming analysis. In this paper, humming is generated without a metronome. Then based on the estimated chord sequence, accompaniment is generated using the MIDI template matched to each chord. The 5 Genre is supported in the music creation. The melody transcription is evaluated in terms of onset and pitch estimation accuracy and MOS evaluation is used for created music evaluation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.12
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• pp.1738-1741
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• 2019

Music performance techniques have been primarily trained by apprenticeship. The technique transfer, which relies on the imitation of experience and actual performance without scientific evidence, required the pianists more time and effort than necessary. However, if the players in the field discover the principles of universally applicable piano playing techniques in collaboration with scientists, they will avoid errors and prepare a new paradigm in the development of piano playing techniques. This is why music performance science is needed. Little has been studied about it in Korea, but it has been activated abroad since the mid-1990s. The core science of music performance science is expected to be computer science fitting data analysis. In this paper, we introduce music performance science for the pianist and present how computer can help it.

• Knowledge Management Research
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• v.19 no.2
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• pp.91-108
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• 2018

This study mainly focused on measuring the impact of comments for a particular song on the number of streamings and downloads. We modeled multiple regression equations to perform this analysis. We chose digital music market for the object of analysis because of its inherent characteristics, such as experience goods, high bandwagon effect, and so on. We carefully utilized text mining technique in accordance with the algorithm of Naïve Bayes classifier to distinguish whether a comment for a piece of music be regarded as positive or negative. In addition, we used 'size of agency' and 'existence of hit song' as moderating variables. The reason for usage of those variables is that those are assumed to affect users' decision for selecting particular song especially when downloading or streaming via music sites. We found empirical evidences that positive comments for a particular song increase the number of both downloads and streamings. However, positive comments may decrease the number of downloads when the size of agency of the artist is big. As a result, we were able to say that a positive comment for a particular song functioned as 'word-of-mouth' effect, inducing other users' behavioral response. We also found that other features of an artist such as size of the agency that the artist belongs to functioned as an external factor along with feature of the song itself.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.6
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• pp.239-244
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• 2009

Digital Music Industry of Korea has had its dominance over existing Record-based Music Industry since the year 2000 influencing the entire music industry. This implies the perspective for this emerging field by defining various factors based on environmental analysis. SWOT analysis, mostly used for setting up the marketing strategy is very useful analytic tool for this manner. The potentials and possibilities were saught for this emerging Digital Music Industry to have connectivity with other Media and Entertainment Industry, focusing on its strength, weakness, opportunities and threats, four variables of SWOT analysis.

• The Journal of Economics, Marketing and Management
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• v.12 no.1
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• pp.89-96
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• 2024

Purpose: This study explored the impact of using a music and horticultural therapy program on depression among rural seniors living in Yeongam-gun and conducted a comparative analysis before and after the program to present basic data helpful for an integrated mental health promotion program tailored to rural areas. Research methodology: The analysis subjects of this study were users of the rural residential program of 'Our Village Day Care Center' in Yeongam-gun in 2023, with a total of 20 people, 10 seniors for each program. The research analysis used SPSS to determine the effect on participation and depression before and after the program was implemented. Results: As a result of the analysis, depression levels decreased after completion of the horticultural therapy program and music therapy program, and this was statistically significant. Conclusion: Three implications are presented based on the following research results. First, the need for programs that can improve not only the physical health but also the mental health of elderly people living in rural areas is suggested. Second, the need for programs that link cultural programs such as music and gardening activities with welfare programs is suggested. Third, the need for follow-up management and verification of periodic mental health checkups for rural elderly is suggested.

• Information Systems Review
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• v.16 no.3
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• pp.49-68
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• 2014

These days, consumers have increasingly preferred to digital real-time streamlining and downloading to listen to music because this is convenient and affordable for the consumers. Accordingly, sales of music in compact disk formats have steadily declined. In this regards, online digital music has become a new communication channel to listen musics, where digital files can be delivered over various online networks to people's computing devices. The majority of online digital music distributors has Music Recommender Systems for sales of digital music on their websites. Music Recommender Systems are parts of information filtering systems that provide the ratings or preferences that users give to music. Korean online digital music distributors have Music Recommender Systems. But those online music distributors didn't provide any rules or clear procedures that recommend music. Therefore, we raise important questions as follows: "Is Music Recommender Systems Fair?", "What is the impact of Music Recommender Systems on online music rankings and sales?" While previous studies have focused on usefulness of Music Recommender Systems, this study investigates not only fairness of Current Music Recommender Systems but also Relationship between Music Recommender Systems and online Music Charts. This study examines these issues based on Bandwagon effect, ranking effect, Slot effect theories. For our empirical analysis, we selected the most famous five online digital music distributors in terms of market shares. We found that all recommended music is exposed to the top of 'daily music charts' in online digital music distributors' websites. We collected music ranking data and recommended music data from 'daily music chart' during a one month. The result shows that online music recommender systems are not fair, since they mainly recommend particular music that supported by a specific music production company. In addition, the recommended music are always exposed to the top of music ranking charts. We also find that recommended music usually appear at the top 20 ranking charts within one or two days. Also, the most music in the top 50 or 100 ranks are the recommended music. Moreover, recommended music usually remain the ranking charts more than one month while non-recommended music often disappear at the ranking charts within two week. Our study provides an important implication to online music industry. Because music recommender systems and music ranking charts are closely related, music distributors may improperly use their recommender systems to boost the sales of music that related to their own companies. Therefore, online digital music distributor must clearly announce the rules and procedures about music recommender systems for the better music industry.

• Research in Community and Public Health Nursing
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• v.9 no.2
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• pp.336-349
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• 1998

The purpose of this study was to test the effects of music therapy on cognitive function and depression in demented old adults. This study was made with one -group in a pre- and post-test design. The subjects were seven demented old adults over, sixty-five years and with mild to moderate cognitive impairment, residing at a nursing home. Music therapy was given by one researcher and one research assistant for thirty to forty minutes twice a week for 4 months. Music therapy was conducted with the subjects both listening and singing with a cassette player and a double-handed drum. In order to evaluate the effects of music, we measured the level of cognitive function and depression at the beginning and at the end of the music therapy session by means of an MMSE- K developed by Kwon and Park and the Depression Inventory developed by Chon. The Data were analyzed using descriptive statistics and a paired t - test analysis using a SPSS PC package. The results are as follows: 1) The subjects of the music therapy showed improvement in cognitive function. The MMSE-K score was significantly increased after music therapy. Especially, memory recall was very significantly. 2) The subjects of the music therapy showed a slight decrease in depression. However, there was no significant difference in the degree of depression between mean scores measured before and after music therapy. The results suggest that music therapy is effective in improving and maintaining cognitive function in demented old adults. And we suggest that long-term music therapy will be required to improve depression in demented old adults. These findings are encouraging the idea that music therapy may improve cognitive impairment.

• The KIPS Transactions:PartB
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• v.17B no.4
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• pp.263-274
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• 2010

To provide context-aware music recommendation service, first of all, we need to catch music mood that a user prefers depending on his situation or context. Among various music characteristics, music mood has a close relation with people‘s emotion. Based on this relationship, some researchers have studied on music mood detection, where they manually select a representative segment of music and classify its mood. Although such approaches show good performance on music mood classification, it's difficult to apply them to new music due to the manual intervention. Moreover, it is more difficult to detect music mood because the mood usually varies with time. To cope with these problems, this paper presents an automatic method to classify the music mood. First, a whole music is segmented into several groups that have similar characteristics by structural information. Then, the mood of each segments is detected, where each individual's preference on mood is modelled by regression based on Thayer's two-dimensional mood model. Experimental results show that the proposed method achieves 80% or higher accuracy.