• KIPS Transactions on Software and Data Engineering
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• v.7 no.6
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• pp.239-248
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• 2018

Many new technologies are studied with the arrival of the 4th industrial revolution. In particular, emotional intelligence is one of the popular issues. Researchers are focused on emotional analysis studies for music services, based on artificial intelligence and pattern recognition. However, they do not consider how we recommend proper music according to the specific emotion of the user. This is the practical issue for music-related IoT applications. Thus, in this paper, we propose an probability-based music emotion classification technique that makes it possible to classify music with high precision based on the range of emotion, when developing music related services. For user emotion recognition, one of the popular emotional model, Russell model, is referenced. For the features of music, the average amplitude, peak-average, the number of wavelength, average wavelength, and beats per minute were extracted. Multiple regressions were derived using regression analysis based on the collected data, and probability-based emotion classification was carried out. In our 2 different experiments, the emotion matching rate shows 70.94% and 86.21% by the proposed technique, and 66.83% and 76.85% by the survey participants. From the experiment, the proposed technique generates improved results for music classification.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.14-19
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• 1997

Emotional intelligence and aesthetic aspects of traditional Korean music, Kuk Ak, are investigated in terms of fractal relationship. The exploration of Kuk Ak in the view of an intelligence paradigm will restore the balanced sense of art and science which seeks happiness in life.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.130-133
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• 1996

An exploration for an emotional intelligence paradigm has been delineated. Emotional intelligence is investigated in terms of composing machine as a modern abstract art. The system consists of interface, plan and performance modules. Design concepts of the system are modular, open, and user friendly to ensure the overall performance. The exploration of art in the view of intelligence, information and structure will restore the balanced sense of the art and the science seek the happiness of life. The investigations of emotional intelligence will establish the foundations of intelligence, information and control technologies.

• Journal of the Korea Society of Computer and Information
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• v.25 no.6
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• pp.25-33
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• 2020

In this paper, the purpose is to verify the impact of performance expectations, effort expectations, social impact, individual innovation and perceived value on the intent of use and the behavior of use. Used Unified Theory of Acceptance and Use of Technology (UTAUT) to verify the applicability of this model in China, and established the research model by adding two new variables to UTAUT according to the situation of the Chinese market. To achieve this goal, 345 questionnaires were collected for experienced music creators using artificial intelligence nuggets in China by means of Internet research. The collected data were analyzed through frequency analysis, factor analysis, reliability analysis, and structural equation analysis through SPSS V. 22.0 and AMOS V 22.0. The verification of the hypotheses presented in the research model identified the decisive influence factors on the use of artificial intelligence music acceptance by Chinese users. The study is innovative in that it attempts to verify the applicability of UTAUT in the Chinese context. In the construction of the user acceptance model of AI music, three influencing factors will have an effect on users' intentions, and according to the degree of effect, from largest to smallest, they are respectively Perceived Innovativeness, Performance Expectancy and Effort Expectancy. This paper will also provide some management advices, i.e. improving the utility and usability of AI music, encouraging users with individual innovativeness, developing competitive and attractive pricing policies, increasing publicity, and prioritizing word-of-mouth advertising.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.12
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• pp.1738-1741
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• 2019

Music performance techniques have been primarily trained by apprenticeship. The technique transfer, which relies on the imitation of experience and actual performance without scientific evidence, required the pianists more time and effort than necessary. However, if the players in the field discover the principles of universally applicable piano playing techniques in collaboration with scientists, they will avoid errors and prepare a new paradigm in the development of piano playing techniques. This is why music performance science is needed. Little has been studied about it in Korea, but it has been activated abroad since the mid-1990s. The core science of music performance science is expected to be computer science fitting data analysis. In this paper, we introduce music performance science for the pianist and present how computer can help it.

• 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 Distribution Science
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• v.22 no.6
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• pp.115-122
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• 2024

Purpose: The main aim of this study is to analyze and suggest new online music distribution models targeted to facilitate the development of the Korean Wave (Hallyu) music market in all locations of the world. This study is conducted through a close analysis of the prevailing distribution models, the unique challenges of the K-pop market, and the trends in new technologies. Research design, data and methodology: To address the issue of how the online music distribution market could be domesticated for the Korean music industry, a systematic review of the previous studies was conducted. The use of the PRISMA approach was followed so that an accurate and transparent method for choosing the studies is ensured. Results: According to the investigation of literature analysis, the online distribution strategy may consist of four key plannings as follows, 1. Leveraging Social Media and User-Generated Content Platforms, 2. Embracing Immersive and Interactive Experiences, 3. Fostering Direct-to-Fan Connections and Monetization, 4. Harnessing Artificial Intelligence and Big Data Analytics. Conclusions: Finally, collaboration and strategic partnerships will be vital. The Korean music companies should seek to cooperate with the technology companies, social media platforms, and the global music streaming services so that they can grow their market, acquire new technologies, and to better their online distribution strategies.

• Lingua Humanitatis
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• v.2 no.1
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• pp.287-301
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• 2002

Either in music or in language, sound plays its role by taking up the fixed multi-spaces in one's consciousness. Music space differs from auditory space whose aim Is to perceive the positions and identities of the outer things. While auditory space is based on the interests of the outer things, music space is based on the indifference. We discuss the notion of space because it is where symbols reside. Categorial perception about the phonemic restoration describes the ability of a listener how to use his own intelligence to acknowledge and fill the missing points; however, musical perception can be explained as a positive regression to avoid colloquial logic and danger of segmentation in the course of auditory experience and phonation acquisition by an infant. About the question on the difference of the listening to the language sound and other sound, auditory mechanism proceeds language sound the same as other types of sound. But there are another theories which claim that brain proceeds the farmer differently from the latter. The function of music has not been discovered as clear as that of language; music has much more meanings in comparison with language.

• Journal of Fisheries and Marine Sciences Education
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• v.20 no.2
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• pp.266-285
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• 2008

This study investigated the relationship between musical understanding and expression, the purpose of music education. It also intended to present the theoretical basis of integrated early childhood music education by examining into the necessity of it as a method to help young children with musical understanding and expression. The results of the study showed that either of the understanding and expression of music should be necessary and there is a mutual promotional relationship between them. It was found out that real musical understanding can be formed not by mechanical skill, but when the relationship between notes is understood with various experiences. Therefore an integrated early childhood music education became necessary as a principle of educational method to help young children with musical understanding and musical expression. Concretely it was found out to be necessary in terms of the characteristics, interest and concern of young children, the use and development of multi intelligence and the translation of the same knowledge into the same level.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2021.06a
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• pp.23-25
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• 2021

This paper describes an approach of composing music with multiple AI composers. This approach enriches more the creativity space of artificial intelligence music composition than using only one composer. This paper presents a simple example with 2 different deep learning composers working together for composing one music. For the experiment, the two composers adopt the same deep learning architecture of an LSTM model trained with different data. The output of a composer is a sequence of notes. Each composer alternatively appends its output to the resulting music which is input to both the composers. Experiments compare different music generated by the proposed multiple composer approach with the traditional one composer approach.