• Title/Summary/Keyword: generative music

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Chord-based stepwise Korean Trot music generation technique using RNN-GAN (RNN-GAN을 이용한 코드 기반의 단계적 트로트 음악 생성 기법)

  • Hwang, Seo-Rim;Park, Young-Cheol
    • The Journal of the Acoustical Society of Korea
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    • v.39 no.6
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    • pp.622-628
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    • 2020
  • This paper proposes a music generation technique that automatically generates trot music using a Generative Adversarial Network (GAN) model composed of a Recurrent Neural Network (RNN). The proposed method uses a method of creating a chord as a skeleton of the music, creating a melody and bass in stages based on the chord progression made, and attaching it to the corresponding chord to complete the structured piece. Also, a new chorus chord progression is created from the verse chord progression by applying the characteristics of a trot song that repeats the structure divided into an individual section, such as intro, verse, and chorus. And it extends the length of the created trot. The quality of the generated music was specified using subjective evaluation and objective evaluation methods. It was confirmed that the generated music has similar characteristics to the existing trot.

Music Generation using Generative Adversarial Network (GAN 알고리즘을 이용한 음악 생성)

  • Im, Hong-Gab;Lee, Sung-Yoen;Shim, Jae-Heon;Lee, Se-Hoon
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2018.07a
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    • pp.397-398
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    • 2018
  • 본 논문에서는 음악 전공자가 아니어도 원하는 악기를 선택하여 손쉽게 자신의 음악을 만들 수 있는 GAN(Generative Adversarial Network) 알고리즘 기반 음악생성 프로그램을 개발하였다. 음악분야는 진입장벽이 높아 음악 전공자가 아니면 자신만의 음악을 제작하기 힘들다. 행사나 소소한 이벤트에서도 쓸 수 있는 자신만의 음악, 방송이나 1인 미디어 등에서도 저작권 걱정 없이 쓸 수 있는 자신만의 음악을 이 GAN 알고리즘 기반 음악생성 프로그램을 이용하여 비전공자라도 손쉽게 음악을 만들 수 있다.

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Deep Learning Music Genre Classification System Model Improvement Using Generative Adversarial Networks (GAN) (생성적 적대 신경망(GAN)을 이용한 딥러닝 음악 장르 분류 시스템 모델 개선)

  • Bae, Jun
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.24 no.7
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    • pp.842-848
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    • 2020
  • Music markets have entered the era of streaming. In order to select and propose music that suits the taste of music consumers, there is an active demand and research on an automatic music genre classification system. We propose a method to improve the accuracy of genre unclassified songs, which was a lack of the previous system, by using a generative adversarial network (GAN) to further develop the automatic voting system for deep learning music genre using Softmax proposed in the previous paper. In the previous study, if the spectrogram of the song was ambiguous to grasp the genre of the song, it was forced to leave it as an unclassified song. In this paper, we proposed a system that increases the accuracy of genre classification of unclassified songs by converting the spectrogram of unclassified songs into an easy-to-read spectrogram using GAN. And the result of the experiment was able to derive an excellent result compared to the existing method.

Secure Coding for SQL Injection Prevention Using Generative AI

  • Young-Bok Cho
    • Journal of the Korea Society of Computer and Information
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    • v.29 no.9
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    • pp.61-68
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    • 2024
  • In this paper, Generative AI is a technology that creates various forms of content such as text, images, and music, and is being utilized across different fields. In the security sector, generative AI is poised to open up new possibilities in various areas including security vulnerability analysis, malware detection and analysis, and the creation and improvement of security policies. This paper presents a guide for identifying vulnerabilities and secure coding using ChatGPT for security vulnerability analysis and prediction, considering the application of generative AI in the security domain. While generative AI offers innovative possibilities in the security field, it is essential to continuously pursue research and development to ensure safe and effective utilization of generative AI through in-depth consideration of ethical and legal issues accompanying technological advancements.

Audio Generative AI Usage Pattern Analysis by the Exploratory Study on the Participatory Assessment Process

  • Hanjin Lee;Yeeun Lee
    • 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.

Metaverse business research for revitalizing the music ecosystem in the web 3.0 era: Focusing on strategies for building music platform (웹 3.0 시대 음악 생태계 활성을 위한 메타버스 비즈니스연구: 음악 플랫폼의 발전 양상 및 구축 전략을 중심으로)

  • Jiwon Kim;Yuseon Won
    • 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.

Impact of Artificial Intelligence on the Development of Art Projects: Opportunities and Limitations

  • Zheng, Xiang;Xiong, Jinghao;Cao, Xiaoming;Nazarov, Y.V.
    • 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.

Analysis of Generative AI Technology Trends Based on Patent Data (특허 데이터 기반 생성형 AI 기술 동향 분석)

  • Seongmu Ryu;Taewon Song;Minjeong Lee;Yoonju Choi;Soonuk Seol
    • 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.

An Automatic Rhythm and Melody Composition System Considering User Parameters and Chord Progression Based on a Genetic Algorithm (유전알고리즘 기반의 사용자 파라미터 설정과 코드 진행을 고려한 리듬과 멜로디 자동 작곡 시스템)

  • Jeong, Jaehun;Ahn, Chang Wook
    • Journal of KIISE
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    • v.43 no.2
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    • pp.204-211
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    • 2016
  • In this paper, we propose an automatic melody composition system that can generate a sophisticated melody by adding non-harmony tone in the given chord progression. An overall procedure consists of two steps, which are the rhythm generation and melody generation parts. In the rhythm generation part, we designed new fitness functions for rhythm that can be controlled by a user setting parameters. In the melody generation part, we designed new fitness functions for melody based on harmony theory. We also designed evolutionary operators that are conducted by considering a musical context to improve computational efficiency. In the experiments, we compared four metaheuristics to optimize the rhythm fitness functions: Simple Genetic Algorithm (SGA), Elitism Genetic Algorithm (EGA), Differential Evolution (DE), and Particle Swarm Optimization (PSO). Furthermore, we compared proposed genetic algorithm for melody with the four algorithms for verifying performance. In addition, composition results are introduced and analyzed with respect to musical correctness.

A Study on the generative background and Characteristics of Gesamtkunstwerk Design Theory advocated by Wiener Werkstätte and Josef Hoffmann (빈 공방과 요제프 호프만이 주창한 총체예술(Gesamtkunstwerk) 디자인론의 생성배경과 특성에 관한 연구)

  • Kim, Hong-Ki
    • Korean Institute of Interior Design Journal
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    • v.25 no.1
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    • pp.115-123
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    • 2016
  • In the turn of the twentieth century, Vienna emerged as a great cultural centre that stood at the forefront of developments in music, psychology, and the natural sciences. Equally influential, and still tremendously popular today, are the designs of the Wiener $Werkst{\ddot{a}}tte$ a group that was at the heart of the city's cultural scene and whose collaborators included such luminaries as the architect Josef Hoffman and the designer Koloman Moser under the slogan of Gesamtkunstwerk. The term "Gesamtkunstwerk" was introduced in the romantic period. It describes the desire for and practice of combining various art forms into a whole, such as performances that combine text, visual arts, various design and architecture. Richard Wagner was one of the early theorists of the concept, inspiring many modernist artists. As a co-founder of the Wiener $Werkst{\ddot{a}}tte$, Josef Hoffmann had a decisive influence on modern Viennese architecture and Interior design on the basis of the concept of Gesamtkunstwerk. In this view point, this study is to analyze about the generative background and design characteristics of gesamtkunstwerk advocated Wiener $Werkst{\ddot{a}}tte$. Josef Hoffmann was by all accounts a very successful architect and Interior designer in Vienna. His influence would undoubtedly have been felt simply because of his talent and energy. His special ability to range across multiple domains, coupled with a willingness to collaborate with other artists has created a synthesis and synergy that is compelling to this day.