• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.1
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• pp.417-420
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• 2005

This report shows the new music player's system which could separate music's tempo by analysis Peak level frequency by time from some percussion instruments. After this process, the new music player could classify some fast or slow genre's musics without a user's order, then we should listen to a fast or slow genre's music by a button.

• Korean Journal of Oriental Medicine
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• v.8 no.1
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• pp.27-43
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• 2002

The aim of this study is to find out the relationships between the vocal sounds and physiologie and pathologic mechanisms based on the Eum-yang and five phases theory[陰陽五行論]. Firstly, concrete characters of vital rhythm of five-viscera were analyzed and patterns of the five-note in oriental music were converted into that of western music, then it was investigated, the possibility of oriental music therapy using sounds as stimulation methods like herbs, acupuncture, and moxibustion. In conclusion, it was found that controlling the Five-visceral vital rhythm by sounds could be used as one of methods for prevention and treatment of disceases, growing on and balancing a body, etc.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.4
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• pp.687-692
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• 2023

This research began with the intention to create music using the superposition characteristics of quantum computers. Existing music has characteristics that are limited to those composed by composers. However, music using the overlap of quantum computers has musical characteristics that change when executed within a limited range. Using this, you will be able to create music that changes based on specific chords at run time. In this paper, quantum computers and existing computers are connected to generate sound, And it focuses on creating changing sounds by applying the nature of superposition.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.2
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• pp.218-223
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• 2011

Various research studies are underway to explore music classification by genre. Because sound professionals define the criterion of music to categorize differently each other, those classification is not easy to come up clear result. When a new genre is appeared, there is onerousness to renew the criterion of music to categorize. Therefore, music is classified by emotional adjectives, not genre. We classified music by light and shade in precedent study. In this paper, we propose the music classification system that is based on emotional adjectives to suitable search for atmosphere, and the classification criteria is three kinds; light and shade in precedent study, intense and placid, and grandeur and trivial. Variance Considered Machines that is an improved algorithm for Support Vector Machine was used as classification algorithm, and it represented 85% classification accuracy with the result that we tried to classify 525 songs.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.1
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• pp.89-94
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• 2021

In this paper, we presented the results of analysis with data obtained through EEG measurements to confirm the effect of musical stimulus when performing mathematical tasks. While the subject was solving a mathematical task, favorite and unfavorite music classified according to the subject's preference were presented as musical stimulus and the tasks were divided into memorization task and procedure task. The data measured in the EEG experiments was divided into theta waves, SMR waves and mid-beta waves which are the frequency bands related to concentration to compare the relative power spectrum values. In our results, in the case of comparing no music with favorite music and no music with unfavorite music, a significant difference was observed in the several channels, and the average difference was shown in the channels F3 and F4 of the frontal lobe. In that channels, the power was found to be greater when the music was presented than the case where there was no music. Depending on the subject's preference, it was confirmed that favorite music showed greater brain activity than unfavorite music.

• International journal of advanced smart convergence
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• v.6 no.2
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• pp.9-15
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• 2017

According to a recent survey, most elementary and secondary school students nationwide are stressed out by their academic records. Furthermore most of high school students in Korea have to study under the great duress. Some of them who can't overcome the academic stress finalize their life by suiciding. A study has found that it is one of the leading causes of stimulating the thought of committing suicide in Korean high school students. So it is necessary to reduce the high school student's suicide rate. Main content of this research is to implement a personalized music recommendation system. Music therapy can help the student deal with the stress, anxiety and depression problems. Proposed system works as a therapist. The music choice and duration of the music is adjusted based on the student's current emotion recognized automatically from EEG. If the happy emotion is not induced by the current music, the system would automatically switch to another one until he or she feel happy. Proposed system is personalized brain music treatment that is making a brain training application running on smart phone or pad. That overcomes the critical problems of time and space constraints of existing brain training program. By using this brain training program, student can manage the stress easily without the help of expert.

• IEMEK Journal of Embedded Systems and Applications
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• v.18 no.5
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• pp.217-223
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• 2023

In this paper, we propose a new model for the conditional generation of music, considering key and rhythm, fundamental elements of music. MIDI sheet music is converted into a WAV format, which is then transformed into a Mel Spectrogram using the Short-Time Fourier Transform (STFT). Using this information, key and rhythm details are classified by passing through two Convolutional Neural Networks (CNNs), and this information is again fed into the Music Transformer. The key and rhythm details are combined by differentially multiplying the weights and the embedding vectors of the MIDI events. Several experiments are conducted, including a process for determining the optimal weights. This research represents a new effort to integrate essential elements into music generation and explains the detailed structure and operating principles of the model, verifying its effects and potentials through experiments. In this study, the accuracy for rhythm classification reached 94.7%, the accuracy for key classification reached 92.1%, and the Negative Likelihood based on the weights of the embedding vector resulted in 3.01.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.419-420
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• 2007

In this method, we extract peak periods using energy contents of each segment of music. This feature extraction method is equally applied on both the training and query music. Similarity matching algorithm is applied on the extracted feature values for identifying the query music from the database. The retrieval accuracy of 95% of our method is a pretty good result.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.10
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• pp.3673-3679
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• 2010

This study is prepared to suggest how to develop sight-singing and ear-training program for applied music-major students. Starting from analysing the internal environment and currently existing materials, based on the questions collected for applied music-major students, integrated program for sight-singing and ear-training was considered. The use of the various kinds of classical and popular music literature, the examples of improvisation in rhythm and harmony, based on the music theories, are focal points of this program recommended here with.

• Proceedings of the Korean Information Science Society Conference
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• 2007.06c
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• pp.252-257
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• 2007

MusicXML은 다양한 전자악보 형식들이 음악을 악보로 표현하는데 있어 지니는 한계를 잘 극복하면서 응용성, 확장성 및 공개성 등의 장점으로 인해 현재 전자악보의 표준으로 가장 적합한 것으로 평가되고 있는 악보 형식이다. 그러나 MusicXML은 XML을 기반으로 한 텍스트 데이터이기 때문에 이러한 악보 형식을 실제 악보로 변환하거나 연주하는 것은 물론 실제 악보 내용을 기반으로 한 악보 검색이 용이하도록 적절한 데이터 구조로 표현하는 것이 필요하다. 본 논문에서는 MusicXML 악보에 대하여 다차원 속성 정보를 가진 데이터의 표현에 용이한 k-d 트리 기반 데이터 구조로 표현하는 방법을 제안한다. 논문은 또한 악보에 대한 k-d 트리 구조를 보다 다양한 응용에 활용할 수 있도록 k-d 트리를 확장하여 구조화하는 방법을 제시한다. 본 논문에서 제안한 방법은 특히 내용을 기반으로 한 악보 정보 검색에 유용하게 이용될 수 있다.