• Architectural research
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• v.23 no.3
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• pp.39-48
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• 2021

Inspiration plays an essential role in architectural design process that compels architects to bring their ideas into final product by engaging in creative thinking. The relation in between architecture and music has been one of combination throughout architectural history used as inspirations for façade's forms and shapes, space configurations and arrangements, and etc. Applying music in architecture produces creative and scientific design methods, provides attractions for visitors, and reflects the social and cultural identities and changes of the particular period. This research aims to analyze the correlations between architecture and music in depth, and examine the perception of musically inspired architecture by empirical study. Five buildings that applied musical rhythms were chosen for survey questionnaires in order to observe how people majoring in architecture, music, and other fields perceive musically inspired architecture differently by matching the music with the building that correlate to each other. By examining the reasons that the respondents have selected such music with a building from the questionnaires, the keywords are extracted and interpreted. The results showed that it is possible for people to perceive music from architecture, and that it is suitable to use music as a source of inspiration in architectural designs.

• Journal of the Korea Society of Computer and Information
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• v.19 no.2
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• pp.77-90
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• 2014

In the past composers used to make music with classical instruments such as piano, violin, guitar, flute, drums, and other well-known tools. With the advent of digital technology many software programs were developed which allow musicians to compose tunes using personal computers. Many file formats were introduced such as NIFF, SMDL and MIDI but none besides MIDI has been successful. Recently MusicXML has emerged as a de-facto standard for the computer representation of music. This paper presents a brief description of the structure of the MusicXML format and describes the development of a music score editor based on MusicXML. We implemented a MusicXML-based score editing software using C# language and a feasibility test showed the efficiency of our proposed method.

• Journal of Korea Multimedia Society
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• v.24 no.8
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• pp.1184-1191
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• 2021

In a pop song, the creator's intention is communicated to the user through music and lyrics. Lyric meaning is as important as music, but in most cases lyrics are delivered to users in a static form without non-verbal cues. Providing lyrics in a static text format is inefficient in conveying the emotions of a music. Recently, lyrics video with kinetic typography are increasingly provided, but producing them requires expertise and a lot of time. Therefore, in this system, the emotions of the lyrics are found through the analysis of the text of the lyrics, and the deep learning model is trained with the data obtained by converting the melody into a Mel-spectrogram format to find the appropriate emotions for the music. It sets properties such as motion, font, and color using the emotions found in the music, and automatically creates a kinetic typography video. In this study, we tried to enhance the effect of conveying the meaning of music through this system.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.146-149
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• 2014

In this paper, humming based automatic music creation method is described. It is difficult for the general public which does not have music theory to compose the music in general. However, almost people can make the main melody by a humming. With this motivation, a melody and chord sequences are estimated by the humming analysis. In this paper, humming is generated without a metronome. Then based on the estimated chord sequence, accompaniment is generated using the MIDI template matched to each chord. The 5 Genre is supported in the music creation. The melody transcription is evaluated in terms of onset and pitch estimation accuracy and MOS evaluation is used for created music evaluation.

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

• Journal of Biomedical Engineering Research
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• v.29 no.4
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• pp.329-336
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• 2008

Recently, causality analysis of source time series extracted from EEG or MEG signals is becoming of great importance in human brain mapping studies and noninvasive diagnosis of various brain diseases. Two approaches have been widely used for the analyses: one is independent component analysis (ICA), and the other is multiple signal classification (MUSIC). To the best of our knowledge, however, any comparison studies to reveal the difference of the two approaches have not been reported. In the present study, we compared the performance of the two different techniques, ICA and MUSIC, especially focusing on how accurately they can estimate and separate various brain electrical signals such as linear, nonlinear, and chaotic signals without a priori knowledge. Results of the realistic simulation studies, adopting directed transfer function (DTF) and Granger causality (GC) as measures of the accurate extraction of source time series, demonstrated that the MUSIC-based approach is more reliable than the ICA-based approach.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.2
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• pp.467-479
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• 2022

Working memory (WM), which plays a vital role in daily activities, is a memory system that temporarily stores and processes information when people are engaged in complex cognitive activities. The influence of music on WM has been widely studied. In this work, we conducted a series of n-back memory experiments with different task difficulties and multiple trials on 14 subjects under the condition of no music and Alpha wave leading music. The analysis of behavioral data show that the change of music condition has significant effect on the accuracy and time of memory reaction (p<0.01), both of which are improved after the stimulation of Alpha wave music. Behavioral results also suggest that short-term training has no significant impact on working memory. In the further analysis of electrophysiology (EEG) data recorded in the experiment, auto-regressive (AR) model is employed to extract features, after which an average classification accuracy of 82.9% is achieved with support vector machine (SVM) classifier in distinguishing between before and after WM enhancement. The above findings indicate that Alpha wave leading music can improve WM, and the combination of AR model and SVM classifier is effective in detecting the brain activity changes resulting from music stimulation.

• Journal of Korea Multimedia Society
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• v.21 no.1
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• pp.45-50
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• 2018

This research paper describes how to summarize music lyrics using the TextRank algorithm. This method can summarize music lyrics as important lyrics. Therefore, we recommend music more effectively than analyzing the number of words and recommending music.

• Journal of Korea Multimedia Society
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• v.23 no.6
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• pp.765-771
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• 2020

To enable AI(artificial intelligence) to realize visual emotions, it attempts to create music centered on color, an element that causes emotions in paintings. Traditional image-based music production studies have a limitation in playing notes that are unrelated to the picture because of the absence of musical elements. In this paper, we propose a new algorithm to set the group of music through the average color of the picture, and to produce music after adding diatonic code progression and deleting sound using median value. And the results obtained through the proposed algorithm were analyzed.