• CELLMED
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• v.8 no.2
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• pp.10.1-10.2
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• 2018

The aims of this article is to examine that Daegeum Sanjo Rhythm (DSR) compare with Jinyang-jangdan and Jajinmori-jangdan on music therapy. Daegeum has the largest range of notes in wind instruments through Korean music. Jangdan is the essential element of rhythm in Korean music. Just as human body sound and resonant with their rhyme and meters, jangdan has its own rhythms of physical structures and sequence and repeat. Jinyang-jangdan, which is close to western minor code, expresses heartbreaking grief and great mourning feeling, so it makes one feel the catharsis through that rhythm. Jinyang-jangdan of daegeum music may be slow, but it can be sublimated into grim music for human. So, people overcome the sadness through grim music. On the other hand, jajinmori-jangdan gives charm and gaiety to people and to everything. So, it is exciting that it's often performed in festival and parade. Rhythmical music is a tool to improve the well-being of humanity and increase our life choices. Therefore, music therapy surely needs both influences of daegeum sanjo music regardless of the rhythm. Because, daegeum sanjo music is nature-friendly music of the rhythm.

• 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.

• Journal of Korea Game Society
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• v.20 no.2
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• pp.75-90
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• 2020

The purpose of this study is to identify the functional role of music, which is one of the main elements that make up PC games. To this end, theme music by genre of PC game was divided through analysis and then the relationship between variables was analyzed by visually positioning the distance between 'music type', 'structural element of music' and 'image' using multiple correspondence matching analysis. As a result, it was confirmed that there was a difference in location between the types of music by game genre, the structural elements of music, and the characteristics of the image.

• The Journal of the Acoustical Society of Korea
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• v.22 no.4E
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• pp.141-149
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• 2003

As music of digital form has been widely used, many people have been interested in the automatic extraction of natural information of music itself, such as key of a music, chord progression, melody progression, tempo, etc. Although some studies have been tried, consistent and reliable results of musical information extraction had not been achieved. In this paper, we propose a method to extract chord and tempo information from general polyphonic music signals. Chord can be expressed by combination of some musical notes and those notes also consist of some frequency components individually. Thus, it is necessary to analyze the frequency components included in musical signal for the extraction of chord information. In this study, we utilize a sinusoidal modeling, which uses sinusoids corresponding to frequencies of musical tones, and show reliable chord extraction results of sinusoidal modeling. We could also find that the tempo of music, which is the one of remarkable feature of music signal, interactively supports the chord extraction idea, if used together. The proposed scheme of musical feature extraction is able to be used in many application fields, such as digital music services using queries of musical features, the operation of music database, and music players mounting chord displaying function, etc.

• The Journal of the Acoustical Society of Korea
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• v.26 no.2E
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• pp.39-43
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• 2007

Music summarization refers to a technique which automatically extracts the most important and representative segments in music content. In this paper, we propose and evaluate a technique which provides the repeated part in music content as music summary. For extracting a repeated segment in music content, the proposed algorithm uses the weighted sum of similarity measures based on multi-level vector quantization for fixed-length summary or optimal-length summary. For similarity measures, count-based similarity measure and distance-based similarity measure are proposed. The number of the same codeword and the Mahalanobis distance of features which have same codeword at the same position in segments are used for count-based and distance-based similarity measure, respectively. Fixed-length music summary is evaluated by measuring the overlapping ratio between hand-made repeated parts and automatically generated ones. Optimal-length music summary is evaluated by calculating how much automatically generated music summary includes repeated parts of the music content. From experiments we observed that optimal-length summary could capture the repeated parts in music content more effectively in terms of summary length than fixed-length summary.

• Journal of Information Processing Systems
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• v.14 no.1
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• pp.32-55
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• 2018

The digitization of music has seen a considerable increase in audience size from a few localized listeners to a wider range of global listeners. At the same time, the digitization brings the challenge of smoothly retrieving music from large databases. To deal with this challenge, many systems which support the smooth retrieval of musical data have been developed. At the computational level, a query music piece is compared with the rest of the music pieces in the database. These systems, music information retrieval (MIR systems), work for various applications such as general music retrieval, plagiarism detection, music recommendation, and musicology. This paper mainly addresses two parts of the MIR research area. First, it presents a general overview of MIR, which will examine the history of MIR, the functionality of MIR, application areas of MIR, and the components of MIR. Second, we will investigate music similarity measurement methods, where we provide a comparative analysis of state of the art methods. The scope of this paper focuses on comparative analysis of the accuracy and efficiency of a few key MIR systems. These analyses help in understanding the current and future challenges associated with the field of MIR systems and music similarity measures.

• International Journal of Advanced Culture Technology
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• v.12 no.3
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• pp.370-379
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• 2024

In this paper, we explore the historical development and revolutionary impact of music in mass media across various forms, including radio, television, film, and digital platforms. The evolution of music in mass media reflects significant technological and cultural shifts over the past century. From the early days of radio to the advent of digital streaming, music has played a crucial role in shaping the types of mass media. Early radio broadcasts in the 1920s relied on live performances and recordings to captivate audiences, establishing music as a central element of media content. The rise of television in the 1950s brought new opportunities for music integration, with theme songs, variety shows, and music videos becoming staples of TV programming. The film industry further revolutionized the use of music, with iconic scores enhancing cinematic storytelling and emotional depth. The digital revolution of the late 20th century introduced new formats and services, expanding access to music and transforming consumption patterns. Recently, streaming platforms and social media allow for personalized music experiences and direct artist-fan interactions. Through an analysis of technological advancements, this study highlights the integral role of music in enhancing narrative, evoking emotions, and creating cultural identities. We present our understanding of this evolution to provide insights into future trends and potential innovations in the integration of music with mass media, including the use of artificial intelligence and virtual reality to create immersive auditory experiences.

• Korean Journal of Child Studies
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• v.20 no.3
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• pp.259-273
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• 1999

This studied investigated children's music identification, classification, and seriation cognitive task performance abilities by age and sex. The subjects were l20 six-, eight-, and ten-year-old school children. There were significant positive correlations among music cognition tasks and significant age and sex differences within each of the music tasks. Ten-year-old children were more likely to complete their music identification tasks than the younger children and girls were more likely than boys to complete their music identification tasks. Eight- and 10-year-old children were more likely to complete their music classification tasks than the younger group. Piagetian stage theory was demonstrated in children's music classification task performance. There was an age-related increase in the performance of the music seriation tasks. Developmental sequential theory was demonstrated in music seriation performance.

• Journal of Information Technology Services
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• v.7 no.3
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• pp.47-70
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• 2008

File sharing technology is the most popular methodology through which consumers gain music from online. However, music file sharing and free downloads of music have caused terrible recession of traditional music industry. The purpose of this paper is to develop the underlying theory for understanding the acceptance of music file sharing technology and empirically test our theoretical model. We develop extended TAM model and explore the influencing factors on the user acceptance of music file sharing technology. Our study delivers a better understanding on consumers’ attitudes towards music downloads. By understanding the fundamental characteristics of technology that makes consumers enthusiastic, traditional music industry will gain managerial implications.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.3
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• pp.159-165
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• 2015

The need for the recognition of music emotion has become apparent in many music information retrieval applications. In addition to the large pool of techniques that have already been developed in machine learning and data mining, various emerging applications have led to a wealth of newly proposed techniques. In the music information retrieval community, many studies and applications have concentrated on tag-based music recommendation. The limitation of music emotion tags is the ambiguity caused by a single music tag covering too many subcategories. To overcome this, multiple tags can be used simultaneously to specify music clips more precisely. In this paper, we propose a novel technique to rank the proper tag combinations based on the acoustic similarity of music clips.