• The Journal of the Convergence on Culture Technology
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• v.9 no.4
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• pp.309-314
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• 2023

This study examines the development and limitations of current artificial intelligence (AI) music composition programs. AI music composition programs have progressed significantly owing to deep learning technology. However, they possess limitations pertaining to the creative aspects of music. In this study, we collect, compare, and analyze information on existing AI-based music composition programs and explore their technical orientation, musical concept, and drawbacks to delineate future directions for AI music composition programs. Furthermore, this study emphasizes the importance of developing AI music composition programs that create "personalized" music, aligning with the era of personalization. Ultimately, for AI-based composition programs, it is critical to extensively research how music, as an output, can touch the listeners and implement appropriate changes. By doing so, AI-based music composition programs are expected to form a new structure in and advance the music industry.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.05a
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• pp.476-479
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• 2020

본 논문은 전기 자극 장치에 관한 것으로서, 운동상황에 맞게 인공지능 기능이 음악을 선별해 주고 음악의 BPM(beats per minute)에 맞게 전기 자극 장치에서의 PWM(pulse width modulation)신호가 동기화 되어 재활 기능과 더불어 헬스 케어와 관련된 추가적인 기능 및 효과를 제공할 수 있는 개선된 전기 자극 장치에 관한 것이다. 언제 어디서나 간편하게 셀프 운동케어와 할 수 있도록 AR기술을 이용한 카메라가 있는 디지털 디바이스를 활용하며, 해당 신체의 운동부위를 지정하게 되면 이에 맞는 운동방법을 AI기술을 이용하여 적용할 수 있다. 수행자가 잘못 운동을 하는 것을 올바르게 개선시키기 위하여 실시간 AI 음성기능과 텍스트 코칭을 통해서 올바르게 운동할 수 있게 제안하며, 이에 대한 과정과 결과를 시각적으로 보여주면, 결과에 대해서는 리포팅을 하여 사용자가 올바르게 운동을 하고 효과적으로 운동을 했는지에 대해서 정량적인 수치의 운동횟수와 운동량에 대해서 표현해준다.

• The Journal of the Korea Contents Association
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• v.20 no.11
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• pp.644-655
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• 2020

The study examined differences between perceptions of AI speakers and intention to continuous use of AI speakers according to usage function. We divided usage patterns into single- and multi-function orientations based on the usage by different functions of audio content (music, news, and search), and analyzed the differences between perceptions of using AI speakers and the intention to continuous use. 335 men and women who had experience using AI speakers participated in an online survey. Results are as follows. First, men used AI speakers mainly for acquiring news, and the extent to which 20s and 40s acquire news was different. Second, perceptions of usefulness and ease of use were found to be higher in the multi-functional group(music-news-search). Last, regarding the intention to continuous use of AI speakers, the multi-functional group was highest, and users focusing on music listening were relatively higher than users for other functions. The findings of the study are expected to be used as foundational data for expanding the use of AI speakers and developing strategies for service provision in each AI speaker brand.

• Broadcasting and Media Magazine
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• v.28 no.2
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• pp.33-42
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• 2023

AI 분야는 기존 분석적(Analytical) AI에서 점차 자가학습을 통한 새로운 디지털 이미지, 영상, 음성, 텍스트, 코드 등을 만드는 Generative AI로 너무 빠르게 진화하고 Generative AI 영역을 두고 세계 각 기업들이 비즈니스의 우위를 선점하기 위해 개발 속도에 열을 올리고 있다. 이미 Generative AI는 다양한 부분에서 활용되고 있는데 음악, 문학, 미디어 등 새로운 창작물을 생성할 뿐만 아니라 향후 지식경제의 생산성을 획기적으로 향상시킬 것이다. 이런 Generative AI가 AI 휴먼 서비스 발전에 어떠한 영향을 미치는지에 대해 논하고자 한다.

• Annual Conference on Human and Language Technology
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• 2020.10a
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• pp.383-388
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• 2020

본 연구에서는 AI 어시스턴트의 음악청취 도메인 내 요청문을 인식 및 처리하기 위해 한국어와 중국어를 중심으로 도메인 사전 및 패턴문법 언어자원을 구축하고 그 결과를 비교분석 하였다. 이를 통해 향후 다국어 언어자원 구축의 접근 방법을 모색할 수 있으며, 궁극적으로 패턴 기반 문법으로 기술한 언어자원을 요청문 인식에 직접 활용하고 또한 주석코퍼스 생성을 통해 기계학습 성능 향상에 도움을 줄 수 있을 것으로 기대된다. 본 연구에서는 우선 패턴문법의 구체적인 양상을 살펴보기에 앞서, 해당 도메인의 요청문 유형의 카테고리를 결정하는 과정을 거쳤다. 이를 기반으로 한국어와 중국어 요청문의 실현 양상과 패턴유형을 LGG 프레임으로 구조화한 후, 한국어와 중국어 패턴문법 간의 통사적, 형태적, 어휘적 차이점을 비교분석 하여 음악청취 도메인 요청문의 언어별 생성 구조 차이점을 관찰할 수 있었다. 구축한 패턴문법은 개체명을 변수(X)로 설정하는 경우, 한국어에서는 약 2,600,600개, 중국어에서는 약 11,195,600개의 표현을 인식할 수 있었다. 결과적으로 본 연구에서 제안한 언어자원의 언어별 차이에 대한 통찰을 통해 다국어 차원의 요청문 인식 자원과 기계학습 데이터로서의 효용을 확인하였다.

• The Journal of the Korea Contents Association
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• v.20 no.5
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• pp.79-89
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• 2020

The current study explored if users' self-relevance of the comparison domain with creative AI robot in music composition affected their envy toward the robot, cognitive assessment toward the music and intention toward working with robot in future. This study conducted a 2 (degree of self-relevance: high(college students majoring in music) vs. low(those not majoring in music) × 2 (working type: robot-only vs. robot-human collaboration) between-subjects factorial design experiment. The findings revealed that those majoring in music did not feel envious of the robot as much as those not majoring in music. However, compared to those not majoring in music, those majoring in music evaluated the robot's creativity lower, had more negative attitude toward the music, showed less intention to use the music and work with the robots in future. No interaction between the degree of self-relevance and the working type was found.

• The Journal of the Convergence on Culture Technology
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• v.9 no.5
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• pp.787-800
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• 2023

This paper is a study aimed at facilitating a comprehensive understanding of the music metaverse platform that will emerge in the era of Web 3.0 and exploring productive strategies for its construction. We examine the significance of the metaverse music platform from various perspectives and investigate the developmental process of digital music platforms from Web 1.0 to 3.0. Subsequently, assuming the emergence of metaverse platforms as a transition to Web 3.0, we align this transition with technological(VR technology, wearable devices, generative AI), cultural(digital avatars, fandom), and economic(NFT) discussions related to Web 3.0. These discussions are integrated with the developmental strategies of the metaverse music platform. Through this study, we hope to enhance the understanding of the metaverse music platform and provide insights into potential construction strategies.

• Trans-
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• v.13
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• pp.117-140
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• 2022

Recently, artificial intelligence technology is being used throughout the industry. Currently, Currently, AI art generators are used in the NFT industry, and works using them have been exhibited and sold. AI art generators in the art field include Gated Photos, Google Deep Dream, Sketch-RNN, and Auto Draw. AI art generators in the music field are Beat Blender, Google Doodle Bach, AIVA, Duet, and Neural Synth. The characteristics of AI art generators are as follows. First, AI art generator in the art field are being used to create new works based on existing work data. Second, it is possible to quickly and quickly derive creative results to provide ideas to creators, or to implement various creative materials. In the future, AI art generators are expected to have a great influence on content planning and production such as visual art, music composition, literature, and movie.

• 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.

• Journal of the Korea Society of Computer and Information
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• v.29 no.4
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• pp.47-54
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• 2024

The importance of cultural arts education utilizing digital tools is increasing in terms of enhancing tech literacy, self-expression, and developing convergent capabilities. The creation process and evaluation of innovative multi-modal AI, provides expanded creative audio-visual experiences in users. In particular, the process of creating music with AI provides innovative experiences in all areas, from musical ideas to improving lyrics, editing and variations. In this study, we attempted to empirically analyze the process of performing tasks using an Audio and Music Generative AI platform and discussing with fellow learners. As a result, 12 services and 10 types of evaluation criteria were collected through voluntary participation, and divided into usage patterns and purposes. The academic, technological, and policy implications were presented for AI-powered liberal arts education with learners' perspectives.