• 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.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.4
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• pp.33-38
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• 2009

This paper proposes an automatic equalizer control method in automobile audio system. The proposed method discriminates the music segment from the consecutive real-time audio stream of the radio and the equalizer is controlled automatically according to the classified genre of the music segment. For enhancing the accuracy of the music genre classification in real-time, timbre feature and rhythm feature extracted from the consecutive audio stream is applied to GMM(Gaussian mixture model) classifier. The proposed method evaluates the performance of the music genre classification, which classified various audio segments segmented from the audio signal of the radio broadcast in automobile audio system into one of five music genres.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.533-536
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• 2015

Mobile music market is growing. However, services what are applied recently are inaccurate to recommend music that a user is worth to prefer. So, this paper suggests music recommend system. This system recommend music that users prefer analyzing music information and user's musical propensity and using collaborative filtering. This system classify genre and extract factors what can be get using STFT's ZCR, Spectral roll-off, Spectral flux. So similar musics are clustered by these factors. And then, after divide mood of music's lyric, it finally recommend music automatically using collaborative filtering.

• Journal of the Korean Institute of Educational Facilities
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• v.13 no.1
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• pp.17-25
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• 2006

Elementary school classroom designs have been developed toward open education system to provide students diverse and improved educational environments since the early of 1990 in Korea. Unfortunately, the quality of music room has not still shown dramatic improvements due to the lack of the acoustical knowledges of architects. This report aims to investigate typical acoustic quality of previous or current music room of elementary schools and show new acoustic treatment technologies to improve the room acoustic of music room by adapting composite perforated panel system and diffusion technology. The music room at Daihyun Elementary school in Yongin was chosen as a case study of this report. The music room was measured to be analyzed using field measurements and the acoustical specifications of composite perforated panel systems and kinds of diffusors were set. Acoustic measurements were performed after the renovation to show the differences between previous room acoustic and after the acoustic renovations. As the result, the case study has shown that the new composite perforated panel systems and diffusion surfaces lowered reverberation time at proper level along with improving the clarity of music, RASTI, and spatial impressions. Also, acoustic interferences such as comb filtering and flutter echoes have been controlled dramatically by diffusive surfaces. The study shows music rooms in elementary schools, middle and high schools can be improved by adapting composite perforated panel systems and diffusors.

• Journal of the Institute of Convergence Signal Processing
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• v.7 no.4
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• pp.189-194
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• 2006

In this paper, design of MUSIC algorithm, which is one of high resolution DOA (direction of arrival) estimation techniques was studied. Generally the complex-valued correlation matrix of MUSIC algorithm is transformed to unitary matrix or matrix expansion for the real hardware implementation. Using the orthogonality between the noise subspace eigenvectors and the steering vectors corresponding to signal component, we estimate DOA with the real-valued computation between steering vectors and noise subspace eigenvectors. The DOA algorithm was designed with VHDL models with considerations of 2 elements and 1 incident wave and its simulation results are derived.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.4
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• pp.188-194
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• 2014

V2I(Vehicular to Infrastructure) is a one kind of communication systems which is used between the base stations and mobile objects. In V2I communication system, it is difficult to obtain the desired communication performance. Beamforming technology is to find the optimal path. and it can be improved the communication performance. MUSIC algorithm can be estimated the direction of arrival. The directional vector of received signals and the eigenvector has orthogonal property. MUSIC algorithm uses this property. In V2I communication environment, real time optimal path is changed. By the high computational complexity of the MUSIC algorithm, the optimal path estimation error is generated. In this paper, we propose a method of computation reduction algorithm for MUSIC algorithm.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.1
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• pp.37-43
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• 2022

This study is a sustainability study of K-Music beyond K-Pop through New Media. New media literally means 'new media'. When TV, classified as legacy media, first appeared in the world, it was an innovative new media platform. Of course, it is considered the most traditional legacy media. However, the definition of new media inevitably changes with the times. Most of the media called new media today are based on online and mobile. This thesis focuses on popular music including crossover traditional music genre. And we define popular music exported abroad as K-pop, and propose the possibility of globalization of Korean music using K-pop users and new media, a metaverse based K-pop audition platform, as consumers and suppliers in the global market. Hallyu, the studying of K-Pop through the study of attitudes and economic effects of K-pop, such as reactions to the spread of K-pop and the reactions of fans who like K-pop, are constantly being discussed in various ways. But there has been no case of cultural technology research that linked the sustainability of Gugak as the Korean music through new media to the K-pop business platform. As the overflowing data pours out in the virtual space as an act that gives the meaning of existence, the online is able to become an open market that provides reliable information all over the world. Therefore we would like to propose on the sustainability of Korean music through the 'Korean Traditional Music Broadcasting Metaverse Audition' beyond the K-pop business model as the K-Music content in the cultural technology era.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.12
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• pp.923-927
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• 2009

The recent growth of a digital music market induces increasing demands for music searching and recommendation services. In order to improve the performance of music-based application services, the process of extracting melodies from polyphonic music is essential. In this paper, we propose a method to extract melodies from piano solo music which is highly polyphonic and has a wide pitch range. We categorize piano music into three classes taking into account the characteristics of music, and extract melodies according to each class. The performance evaluation for the implemented system showed that our method works successfully on a variety of piano solo music.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.18 no.12
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• pp.1352-1358
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• 2007

This paper address the statistical charateristics of MUSIC algorithm which is suggested as satellite direction finding algorithm. If the MUSIC algorithm is adopted as a satellite direction detection method in mobile TT&C system, then the statistical performance of the MUSIC algorithm will be closely related with the overall performance of the system. So statistical characteristics of the parameter in the respect of SNR and data length are addressed and then analyse the final effects to the satellite direction finding.

• Journal of the Institute of Convergence Signal Processing
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• v.11 no.1
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• pp.41-46
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• 2010

In this paper, the DoA(Direction of Arrival) estimator using unitary MUSIC algorithm is studied. The complex-valued correlation matrix of MUSIC algorithm is transformed to the real-valued one using unitary transform for easy implementation. The eigenvalue and eigenvector are obtained by the combined Jacobi-CORDIC algorithm. CORDIC algorithm can be implemented by only ADD and SHIFT operations and MUSIC spectrum computed by 256 point DFT algorithm. Results of unitary MUSIC algorithm designed by System Generator for FPGA implementation is entirely consistent with Matlab results. Its performance is evaluated through hardware co-simulation and resource estimation.