• 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.

• 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.

• 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.

• 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 Venture Innovation
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• v.4 no.1
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• pp.87-99
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• 2021

The importance of "personalization technology" has recently been highlighted due to the Covid-19 and the development of IT technology such as AI and big data, which is soon coming beyond personalization into the "super-personalization era." Therefore, in terms of the music streaming service market, it has formed a service supply trend in which individual tastes are respected and companies are seeking to establish a realistic analysis and development direction considering the external market environment. From this perspective, this paper sought to analyze the strengths and weaknesses of the Genie Music's and provide a direction for development based on Genie Music's customer interactive strategy. In particular, it was intended to analyze the advantages and disadvantages of customer interactive strategies with the 'live music service platform' that moves with customers and to provide directions for future corporate development. As an analysis method, we looked at strengths and weaknesses, opportunities and threat requirements based on SWOT analysis. Afterwards, the company attempted to present specific corporate development strategies through TOWS analysis.

• Trans-
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• v.13
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• pp.35-58
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• 2022

This study predicts the paradigm shift that the development of artificial intelligence technology will bring to the production of music content, and suggests that works created through collaboration between artificial intelligence and humans can have artistic value as finished products. Anyone can easily produce music content using artificial intelligence composition programs, and it has become an opportunity to inspire artists with various attempts and creative ideas. Although artificial intelligence technology provides convenience in human life and benefits a lot in the efficient aspect of work, it is difficult to escape the perception of data-based pattern music in the art field so far. Pattern music with many quantitative elements is not recognized as a complete creation due to the absence of abstract symbolism or meaning pursued by art. However, it predicts that if qualitative elements such as emotions and creativity are given to artificial intelligence music through human collaboration, it can be recognized as a complete work of art. The development of artificial intelligence technology increases access to culture and art from the public, and it can be expected that anyone can enjoy it as well as aesthetic experiences. In addition, various contents can be produced by improving individual digital literacy, and it is an opportunity to share and communicate with others. As such, artificial intelligence technology serves as a medium connecting the public with culture and art, and is narrowing the gap between humans and technology through art activities. Along with this cultural phenomenon, we predict the possibility of research on the production of artificial intelligence music contents with artistic value and the development of various convergence and complex art contents using artificial intelligence technology in the future.

• Journal of Digital Convergence
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• v.19 no.6
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• pp.1-9
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• 2021

Artificial intelligence (AI) devices are rapidly emerging as a core platform of next-generation information and communication technology (ICT), this study investigated consumer usage behavior and user experience through AI devices that are widely applied to consumers' daily lives. To this end, data was collected from 600 consumers with experience in using AI devices were derived to recognize the attributes and behavior of AI devices. The analysis results are as follows. First, music listening was the most used among various attributes and it was found that simple functions such as providing weather information were usefully recognized. Second, the main devices used by AI device users were identified as AI speakers, smartphone, PC and laptops. Third, associative images of AI devices appeared in the order of fun, useful, novel, smart, innovative, and friendly. Therefore, practical implications are suggested to contribute to provision of user services using AI devices in the future by analyzing usage behaviors that reflect the characteristics of AI devices.

• Advanced Industrial SCIence
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• v.1 no.2
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• pp.9-16
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• 2022

This study was a randomized before-and-after design of 17 subjects in the experimental group and 17 subjects in the control group to investigate the effects of listening to relaxing music on the mood state and autonomic nervous system, that is, heart rate of hospitalized patients with mental illness. The collected data were analyzed with SPSS V15.0. There was a statistically significant difference between the two groups in mood state and autonomic nervous system, that is heart rate and the effect of listening to relaxation music was objectively verified(<.05). among the subdomains of mood states, tension(<.00), depression (<.00), vitality (<.03), fatigue () <.01), excluding anger (>.39) and confusion (>.33) showed a significant difference, proving that it is an effective intervention method applied to hospitalized mentally ill patients. In the future, we would like to suggest long-term intervention research and development and application, and research on the effect of mood change and heart rate using individual preferred music.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.1
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• pp.1-9
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• 2024

This paper analyzes the trends in generative AI technology based on patent application documents. To achieve this, we selected 5,433 generative AI-related patents filed in South Korea, the United States, and Europe from 2003 to 2023, and analyzed the data by country, technology category, year, and applicant, presenting it visually to find insights and understand the flow of technology. The analysis shows that patents in the image category account for 36.9%, the largest share, with a continuous increase in filings, while filings in the text/document and music/speech categories have either decreased or remained stable since 2019. Although the company with the highest number of filings is a South Korean company, four out of the top five filers are U.S. companies, and all companies have filed the majority of their patents in the U.S., indicating that generative AI is growing and competing centered around the U.S. market. The findings of this paper are expected to be useful for future research and development in generative AI, as well as for formulating strategies for acquiring intellectual property.

• Science of Emotion and Sensibility
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• v.23 no.2
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• pp.61-74
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• 2020

Voice user interface has become a commercially viable and extensive interaction mechanism with the development of voice assistants. Despite the popularity of voice assistants, the academic community does not utterly understand about what, when, and how users chat with them. Chatting with a voice assistant is crucial as it defines how a user will seek the help of the assistant in the future. This study aims to cover the essence and construct of conversational AI, to develop a classification method to deal with user utterances, and, most importantly, to understand about what, when, and how Chinese users chat with voice assistants. We collected user utterances from the real conventional database of a commercial voice assistant, NetEase Sing in China. We also identified different utterance categories on the basis of previous studies and real usage conditions and annotated the utterances with 17 labels. Furthermore, we found that the three top reasons for the usage of voice assistants in China are the following: (1) greeting, (2) function, and (3) music. Chinese users like to interact with voice assistants at night from 7 PM to 10 PM, and they are polite toward the assistants. The whole percentage of negative feedback utterances is less than 6%, which is considerably low. These findings appear to be useful in voice interaction designs for intelligent hardware.