• Journal of Korea Multimedia Society
• /
• v.16 no.4
• /
• pp.453-463
• /
• 2013

In this paper, we present an effective method and a system for the music summarization which automatically extract the chorus portion of a piece of music. A music summary technology is very useful for browsing a song or generating a sample music for an online music service. To develop the solution, conventional automatic music summarization methods use a 2-dimensional similarity matrix, statistical models, or clustering techniques. But our proposed method extracts the music summary by calculating BER(Bit Error Rate) between audio fingerprint blocks which are extracted from a song. But we could directly use an enormous audio fingerprint database which was already saved for a music retrieval solution. This shows the possibility of developing a various of new algorithms and solutions using the audio fingerprint database. In addition, experiments show that the proposed method captures the chorus of a song more effectively than a conventional method.

• Journal of Convergence for Information Technology
• /
• v.11 no.9
• /
• pp.214-220
• /
• 2021

With the rapid spread of smartphones, it has become common to listen to music everywhere, just like background music in life, so it is necessary to create a music database that can make recommendations according to individual circumstances and conditions. This paper proposes a music recommendation model through social media. Since emotions, situations, time of day, weather, etc. are included in hashtags, it is possible to build a social media-based database that reflects the opinions of various people with collective intelligence. We use web crawling to collect and categorize different hashtags from posts with music title hashtags to use real listeners' opinions about music in a database. Data from social media is used to create a music database, and music is classified in a different way from collaborative filtering, which is mainly used by existing music platforms.

• Journal of Broadcast Engineering
• /
• v.24 no.6
• /
• pp.1024-1034
• /
• 2019

Preference for music is determined by a variety of factors, and identifying characteristics that reflect specific factors is important for music recommendations. In this paper, we propose a method to extract the singing voice related music features reflecting various musical characteristics by using a model learned for singer identification. The model can be trained using a music source containing a background accompaniment, but it may provide degraded singer identification performance. In order to mitigate this problem, this study performs a preliminary work to separate the background accompaniment, and creates a data set composed of separated vocals by using the proven model structure that appeared in SiSEC, Signal Separation and Evaluation Campaign. Finally, we use the separated vocals to discover the singing voice related music features that reflect the singer's voice. We compare the effects of source separation against existing methods that use music source without source separation.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.26 no.7
• /
• pp.1098-1101
• /
• 2022

With the development of computer music notation programs, when drawing sheet music, it is often drawn using a computer. However, there are still many use of hand-written notations for educational purposes or to quickly draw sheet music such as listening and dictating. In previous studies, OMR focused on recognizing the printed music sheet made by music notation program. the result of handwritten OMR with camera is poor because different people have different writing methods, and lens distortion. In this study, as a pre-processing process for recognizing handwritten music sheet, we propose a method for recognizing a staff using linear regression and a method for recognizing a bar using CNN. F₁ scores of staff recognition and barline detection are 99.09% and 95.48%, respectively. This methodologies are expected to contribute to improving the accuracy of handwriting.

• Research in Community and Public Health Nursing
• /
• v.11 no.1
• /
• pp.245-261
• /
• 2000

Based on the literature, status and role the music therapist in America was reviewed for this study. The process of developing a music therapy program in America suggests to us many things: In America, music therapists have sustained a mutually beneficial status with their clients for, over fifty years. Excellence in academic education and clinical training enable music therapists to continue to provide quality music therapy. The magnitude of change in to music therapy in the United States, however creates the challenge of providing real access to music therapy continues in the future. Music therapy is the use of music in the accomplishment of therapeutic aims: the restoration, maintenance, and improvement of mental and physical health. Music therapists work with individuals of all ages who require special services due to behavioral. social. learning, or physical disabilities. Employment may be in hospitals, clinics, day care facilities, schools, community mental health centers, substance abuse facilities, nursing homes, hospices, rehabilitation centers, correctional facilities, or private practices. The American Music Therapy Association (AMTA) was founded in 1998 as a result of a union between the American Association for Music Therapy (founded in 1971) and the National Association for Music Therapy(founded in 1950). Music therapists are highly qualified professionals who have completed approved degree programs and had clinical training in order to receive Board Certification(MT-BC), with the designation of Registered, Certified, or Advanced Certified Music Therapist(RMT. CMT - or ACMT). AMTA provides several mechanism for monitoring the quality of music therapy programs: Standards of Practice. a Code of Ethics, a system for Peer Review, a Judical Review Board, and an Ethics Board. According to the results of this study, the suggestions were as follows: 1. It is concluded that music therapy as a nursing intervention can be effective for the clients. 2. It is a great challenge to develope a music therapy program for nursing intervention however, it is also task and responsibility to further the development of nursing.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.8 no.5
• /
• pp.400-404
• /
• 2015

In this paper, we study for direction of arrival MUSIC spatial spectrum algorithm in order to desired signal estimation in spatial. Proposal MUSIC spatial spectrum algorithm in paper use model error and Bayesian method to estimation on correct target position. Receiver array response vector using adaptive array antenna use Bayesian method, and target position estimate to update weight value with model error method. Target's signal estimation of desired direction of arrival in this paper apply weight value of signal covariance matrix for array response vector after removing incident signal interference and noise, respectively. Though simulation, we analyze to compare proposed method with general method.

• The Journal of the Korea Contents Association
• /
• v.21 no.6
• /
• pp.629-638
• /
• 2021

This study investigated the relationships between ADHD trait, emotional music use, relationship initiation, and expectation for future life in early adolescence, and to verify path model to predict the expectation for future life. The participants were 347 male and female middle school students, their average of ages was 13.35 (SD=.91). The ADHD trait was measured with self-report scale, emotional music use and relationship initiation were measured with sub-scales of Use of Music Inventory and Interpersonal Competence Questionnaire, and expectation for future life was measured with modified items of Satisfaction with Life Scale. Results revealed that ADHD trait was negatively correlated with relationship initiation and expectation for future life, whereas emotional music use was positively correlated with relationship initiation and expectation for future life. And, relationship initiation positively correlated with expectation for future life. The alternative model was adopted that included a direct path from ADHD trait to expectation for future life in the proposed model, rather than the proposed model in which ADHD trait and emotional music use affects expectation for future life through relationship initiation. The findings of this study should provide useful information for further studies and for professionals who try to promote the expectation for future life in early adolescence.

• CELLMED
• /
• v.8 no.4
• /
• pp.22.1-22.5
• /
• 2018

Most modern adults are overweight or obese. Health services are troubling to overcome the large number of individuals in need of weight loss. Music therapy is emerging as a new option. Among various music therapy methods, it studied various treatments through Korean traditional music, and it is thought that Korean traditional music is a good therapy for diet. The present review focused on find the most useful condition for weight control by using Korean traditional music. National Center for Korean Traditional Performing Arts measured the dB of Korean traditional music, In the next, listen to other dB's music while eating and compared energy intake, water intake, duration of meals, number of servings, number of bites, eating rate (bites per minute), and bite size (grams). As a result of the exhibits, differences in food intake were also found in the difference of dB. 60 dB of music showed a decrease in energy intake. It suggests that Korean traditional music belonging to 60 dB brings weight loss effect. As a result, the effect of weight loss is shown by use Korean traditional music. However, future studies should be performed to reduce the energy intake by increasing the exposure period to Korean traditional music

• Journal of Distribution Science
• /
• v.22 no.6
• /
• pp.115-122
• /
• 2024

Purpose: The main aim of this study is to analyze and suggest new online music distribution models targeted to facilitate the development of the Korean Wave (Hallyu) music market in all locations of the world. This study is conducted through a close analysis of the prevailing distribution models, the unique challenges of the K-pop market, and the trends in new technologies. Research design, data and methodology: To address the issue of how the online music distribution market could be domesticated for the Korean music industry, a systematic review of the previous studies was conducted. The use of the PRISMA approach was followed so that an accurate and transparent method for choosing the studies is ensured. Results: According to the investigation of literature analysis, the online distribution strategy may consist of four key plannings as follows, 1. Leveraging Social Media and User-Generated Content Platforms, 2. Embracing Immersive and Interactive Experiences, 3. Fostering Direct-to-Fan Connections and Monetization, 4. Harnessing Artificial Intelligence and Big Data Analytics. Conclusions: Finally, collaboration and strategic partnerships will be vital. The Korean music companies should seek to cooperate with the technology companies, social media platforms, and the global music streaming services so that they can grow their market, acquire new technologies, and to better their online distribution strategies.

• Journal of Digital Convergence
• /
• v.14 no.5
• /
• pp.309-316
• /
• 2016

While consumption patterns have changed online music, online music platform began to emerge. While people prefer popular music recommendation, they use the online music platform chart or use the SNS Platform to share information. Online platform Ranking is different because of different properties held by members. Meanwhile, we need music charts characteristics of SNS users. So there were a lot of attempts to chart a comprehensive variety of platforms. And continue to emerge theses linking the musical characteristics and SNS. In this paper, We have developed a new chart using the behavior of Twitter Users who listen to music, and studies comparing the results with existing chart.