• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.12
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• pp.1726-1733
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• 2019

Movement is everything in life and music is with our whole lives. Based on movement and sound, art has developed and reflected the times with close ties to technology and is creating new cultural content in the digital age. The absence of experts and research institutes with academic knowledge and experience in various fields compared to the frequency with which music and body movements are interwoven in the intermedia art and education of convergence is a real problem. Introducing the Rhythmik that studied the most basic principles of music and exercise through the precedent of foreign universities, we raise the need to introduce music physiology, musicians' Medicine and music performance science, the areas we studied together. It presents a new direction in the convergence era and education in pioneering research areas in which the only "I myself" systematically recognizes the movement to become the subject through physiology and medicine and scientifically moves and expresses music as a medium.

• Proceedings of the Korean Society of Computer Information Conference
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• 2013.07a
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• pp.127-128
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• 2013

최근 'healing'이라는 단어가 여기저기에서 많이 사용되고 있다. 과도한 업무와 스트레스에 지친 직장인들뿐만 아니라 학생들까지도 'healing'을 찾고 있는 추세이다. 그러다 보니 자연스럽게 명상이나 요가, 음악 치료와 같은 심신의 건강, 회복과 정서적인 안정을 위한 여러 가지 활동들을 찾게 되었으며 스마트폰이 발달함에 따라서 지금은 스마트폰의 애플리케이션을 이용하여 쉽고 간편하게 음악 치료를 이용하고 있으며, 두뇌와 비타민의 합성어인 BTamin 음악이 유행처럼 번지게 되며 뇌파 (Bectro Encephaio Graphy : EGG)에 대한 관심도 높아졌다. 본 논문은 안드로이드 마켓의 Music Therapy for sound sleep 애플리케이션의 알파 웨이브 음악을 RightMark Audio Analyzer 프로그램을 통하여 분석 해보았다.

• Journal of the Korean Institute of Telematics and Electronics D
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• v.34D no.6
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• pp.65-74
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• 1997

In this paper, SA-multiplexed filter is designed using SA (simulated ananealing) to recognize music notation patterns varying in size, shape, position and having considerably many similar shapes for optical pattern recognition system. This filter has correlation resutls at wanted location and can identify same class, classify similar class for scale-varianted or rotation-varianted music notation patterns havng learning process. Also, the optimum filter is oriented to analyze on the similar discrimination at acquired position using SA and enhances optical diffractive efficiency as well as peak beam intensity. Compared with POF *(phase only filter), cosine-BPOF(cosine-binary phase only filter), that has excellent discrimination capability even if the different rate is 0.1% quantitatively.

• Proceedings of the Korean Society of Computer Information Conference
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• 2018.07a
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• pp.397-398
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• 2018

본 논문에서는 음악 전공자가 아니어도 원하는 악기를 선택하여 손쉽게 자신의 음악을 만들 수 있는 GAN(Generative Adversarial Network) 알고리즘 기반 음악생성 프로그램을 개발하였다. 음악분야는 진입장벽이 높아 음악 전공자가 아니면 자신만의 음악을 제작하기 힘들다. 행사나 소소한 이벤트에서도 쓸 수 있는 자신만의 음악, 방송이나 1인 미디어 등에서도 저작권 걱정 없이 쓸 수 있는 자신만의 음악을 이 GAN 알고리즘 기반 음악생성 프로그램을 이용하여 비전공자라도 손쉽게 음악을 만들 수 있다.

• The Journal of Society for e-Business Studies
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• v.22 no.3
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• pp.75-85
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• 2017

Personalization recommendations have already proven in many areas of the e-commerce industry. For personalization recommendations, additional work such as reclassifying items is generally necessary, which requires personal information. In this study, we propose a recommendation technique that neither exploit personal information nor reclassify items. We focus on music recommendation and performed experiments with actual music listening data. Experimental analysis shows that the proposed method may result in meaningful recommendations albeit it exploits less amount of data. We analyze the appropriate number of items and present future considerations for contextual recommendation.

• Journal of Information Processing Systems
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• v.13 no.2
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• pp.400-416
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• 2017

Music emotion is an important component in the field of music information retrieval and computational musicology. This paper proposes an approach for automatic emotion classification, based on rough set (RS) theory. In the proposed approach, four different sets of music features are extracted, representing dynamics, rhythm, spectral, and harmony. From the features, five different statistical parameters are considered as attributes, including up to the $4^{th}$ order central moments of each feature, and covariance components of mutual ones. The large number of attributes is controlled by RS-based approach, in which superfluous features are removed, to obtain indispensable ones. In addition, RS-based approach makes it possible to visualize which attributes play a significant role in the generated rules, and also determine the strength of each rule for classification. The experiments have been performed to find out which audio features and which of the different statistical parameters derived from them are important for emotion classification. Also, the resulting indispensable attributes and the usefulness of covariance components have been discussed. The overall classification accuracy with all statistical parameters has recorded comparatively better than currently existing methods on a pair of datasets.

• International Journal of Computer Science & Network Security
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• v.22 no.9
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• pp.343-347
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• 2022

To date, the use of artificial intelligence has already brought certain results in such areas of art as poetry, painting, and music. The development of AI and its application in the creative process opens up new perspectives, expanding the capabilities of authors and attracting a new audience. The purpose of the article is to analyze the essential, artistic, and technological limitations of AI art. The article discusses the methods of attracting AI to artistic practices, carried out a comparative analysis of the methods of using AI in visual art and in the process of writing music, identified typical features in the creative interaction of the author of a work of art with AI. The basic principles of working with AI have been determined based on the analysis of ways of using AI in visual art and music. The importance of neurobiology mechanisms in the course of working with AI has been determined. The authors conclude that art remains an area in which AI still cannot replace humans, but AI contributes to the further formation of methods for modifying and rethinking the data obtained into innovative art projects.

• Journal of Digital Contents Society
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• v.19 no.4
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• pp.829-836
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• 2018

Sheet music is one of the inevitable elements for successful melody interpretation, playing or rendering, and performance, most of performing artists usually utilize a paper sheet music in the cases. However, the paper sheet music can be a one of the reason to degrade the concentration of audiences and artists or entire performing flows. In addition, it might be a weakness to use a paper sheet music in an outside performing place. We propose an electronic sheet music page tuner application, which can overcome these problems, based on a Tablet PC. The proposed page tuner application, which uses the OpenCV to adapt an eye tracking and behavior recognition, can provide an automatical page pass function to the performing artists. We will expect that the proposed application can highly decrease the weakness of paper sheet music.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.1
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• pp.27-32
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• 2019

Research that implements the classification process through Deep Learning algorithm, one of the outstanding human abilities, includes a unimodal model, a multi-modal model, and a multi-modal method using music videos. In this study, the results were better by suggesting a system to analyze each song's spectrum into short samples and vote for the results. Among Deep Learning algorithms, CNN showed superior performance in the category of music genre compared to RNN, and improved performance when CNN and RNN were applied together. The system of voting for each CNN result by Deep Learning a short sample of music showed better results than the previous model and the model with Softmax layer added to the model performed best. The need for the explosive growth of digital media and the automatic classification of music genres in numerous streaming services is increasing. Future research will need to reduce the proportion of undifferentiated songs and develop algorithms for the last category classification of undivided songs.

• Journal of the Korea Computer Graphics Society
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• v.29 no.4
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• pp.1-6
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• 2023

To enhance immersive experiences for metaverse environements, background music is often used. However, the background music is mostly pre-matched and repeated which might occur a distractive experience to users as it does not align well with rapidly changing user-interactive contents. Thus, we implemented a system to provide a more immersive metaverse conversation experience by 1) developing a regression neural network that extracts emotions from an utterance using KEMDy20, the Korean multimodal emotion dataset 2) selecting music corresponding to the extracted emotions from an utterance by the DEAM dataset where music is tagged with arousal-valence levels 3) combining it with a virtual space where users can have a real-time conversation with avatars.