• 제목/요약/키워드: Music Technology

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The Historical Achievement of the South Korean Music Industry

  • Woo-Jun JANG
    • 한류연구
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    • 제3권1호
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    • pp.7-13
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    • 2024
  • The study aims to examine the development of the South Korean music industry over time in order to capture the evolution process of the industry from its initial stages to its current state as one of the world's leading music markets. Based on the above consideration, a systematic literature review was conducted in order to provide an overview of the achievements of the South Korean music industry with the help of PRISMA method. The reason for doing this is to ensure that the process of selecting, filtering and collecting literature from different sources is not only efficient and time-saving but also rigid and coherent. This paper will explore the various elements that have defined the industry, including culture, technology, marketing and government policies and regulations (Jang & Song, 2017). Furthermore, it will inquire the effects of the K-pop cultural export on other industries, whether it be tourism, fashion, consumer goods, and more, thereby illustrating its vast significance. In more detail, this study aims to give an adequate idea about the historical accomplishments of the South Korean music industry in the global music map, identify factors that facilitated the enhancement of the industry and examine the significance of the findings and their applications for the industry's progression and development in the future.

Bayesian Learning through Weight of Listener's Prefered Music Site for Music Recommender System

  • Cho, Young Sung;Moon, Song Chul
    • Journal of Information Technology Applications and Management
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    • 제23권1호
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    • pp.33-43
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    • 2016
  • Along with the spread of digital music and recent growth in the digital music industry, the demands for music recommender are increasing. These days, listeners have increasingly preferred to digital real-time streamlining and downloading to listen to music because it is convenient and affordable for the listeners to do that. We use Bayesian learning through weight of listener's prefered music site such as Melon, Billboard, Bugs Music, Soribada, and Gini. We reflect most popular current songs across all genres and styles for music recommender system using user profile. It is necessary for us to make the task of preprocessing of clustering the preference with weight of listener's preferred music site with popular music charts. We evaluated the proposed system on the data set of music sites to measure its performance. We reported some of the experimental result, which is better performance than the previous system.

Automatic Music Recommendation System based on Music Characteristics

  • Kim, Sang-Ho;Kim, Sung-Tak;Kwon, Suk-Bong;Ji, Mi-Kyong;Kim, Hoi-Rin;Yoon, Jeong-Hyun;Lee, Han-Kyu
    • 한국HCI학회:학술대회논문집
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    • 한국HCI학회 2007년도 학술대회 1부
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    • pp.268-273
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    • 2007
  • In this paper, we present effective methods for automatic music recommendation system which automatically recommend music by signal processing technology. Conventional music recommendation system use users’ music downloading pattern, but the method does not consider acoustic characteristics of music. Sometimes, similarities between music are used to find similar music for recommendation in some method. However, the feature used for calculating similarities is not highly related to music characteristics at the system. Thus, our proposed method use high-level music characteristics such as rhythm pattern, timbre characteristics, and the lyrics. In addition, our proposed method store features of music, which individuals queried, to recommend music based on individual taste. Experiments show the proposed method find similar music more effectively than a conventional method. The experimental results also show that the proposed method could be used for real-time application since the processing time for calculating similarities between music, and recommending music are fast enough to be applicable for commercial purpose.

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A Study on the Sentiment Analysis of Contemporary Pop Musicians and Classical Music Composers

  • Park, Youngjoo
    • International Journal of Advanced Culture Technology
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    • 제10권3호
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    • pp.352-359
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    • 2022
  • The study examined a sentiment analysis based on Tweeter messages between contemporary pop musicians and classical music composers. Musicians of each genre were carefully selected for the sentiment analysis. Many opinion messages on Tweets that users have discussed were collected, and the messages were evaluated by using Naïve Bayes Classifier. The results demonstrated that users showed high positive sentiments for the two different genres. However, on average, the positive sentiment values for classical music composers are higher than for contemporary pop musicians. In addition, the rankings of the highest positive sentiments among contemporary pop musicians and classical music composers did not coincide with the popularity of the two different genres of musicians. This study will contribute to the study of future sentimental analysis between music and musicians.

Development of a Personalized Music Recommendation System Using MBTI Personality Types and KNN Algorithm

  • Chun-Ok Jang
    • International Journal of Advanced Culture Technology
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    • 제12권3호
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    • pp.427-433
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    • 2024
  • This study aims to develop a personalized music digital therapeutic based on MBTI personality types and apply it to depression treatment. In the data collection stage, participants' MBTI personality types and music preferences were surveyed to build a database, which was then preprocessed as input data for the KNN model. The KNN model calculates the distance between personality types using Euclidean distance and recommends music suitable for the user's MBTI type based on the nearest K neighbors' data. The developed system was tested with new participants, and the system and algorithm were improved based on user feedback. In the final validation stage, the system's effectiveness in alleviating depression was evaluated. The results showed that the MBTI personality type-based music recommendation system provides a personalized music therapy experience, positively impacting emotional stability and stress reduction. This study suggests the potential of nonpharmacological treatments and demonstrates that a personalized treatment experience can offer more effective and safer methods for treating depression.

발레 Fouette Turns 동작 시 음악반주 유무에 따른 정면응시도 및 회전축 이동거리 차이 (A Comparative Study on Orientation density to the Front and Path Length of Rotational Axis with/without Music during Fouette Turns)

  • 조남규;오성근;신화경;박재근;이승연;기재석;하종규
    • 한국운동역학회지
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    • 제23권4호
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    • pp.403-407
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    • 2013
  • Fouett$\acute{e}$ turns are repeated pirouettes which begin as a normal pirouette en dehors but include a movement that allows the rotational momentum lost to friction to be regained once each revolution. The purpose of this study was to investigate on orientation density of head/trunk to the front with and without music to which dancers perform the Fouette turn in time. 10 female dancers($21.0{\pm}1.4$ years old, height; $165.3{\pm}3.9$ cm, weight: $50.5{\pm}5.7$ kg) who are the students of S University participated in this study. It took shorter time to perform one revolution of fouette turn with music (930 ms) than without music (961 ms), which reason may be the shorter time of phase 2 in which the rotational momentum is not produced but lost to fiction. Orientation density of trunk to the front was smaller with music (.176) than without music (.196), while the one of head had not significant difference between with and without music. And the path length of marker on $2^{nd}$ left metatarsal bone during one revolution was smaller with music (35.7 cm) than without music (40.2 cm) but the difference was not statistically significant (p=.267).

MyMusicShuffler: 뇌파의 실용적 활용을 통한 감정분석 기반 음악 추천 시스템에 관한 연구 (MyMusicShuffler: Mood-Based Music Recommendation with the Practical Usage of Brainwave Signals)

  • 신사임;장달원;이종설;장세진;김지환
    • 한국정보처리학회:학술대회논문집
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    • 한국정보처리학회 2014년도 추계학술발표대회
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    • pp.1195-1198
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    • 2014
  • 이 논문은 실시간으로 취득되는 뇌파를 기반으로 자동으로 음악을 추천하는 음악추천 기능의 시스템인 MyMusicShuffler 를 소개한다. 이 시스템은 뇌파 분석을 통한 사용자의 감성을 자동으로 분류하는 방식으로 멀티태스킹 환경에 익숙한 사용자들의 음악 청취를 위한 소모적인 상호작용을 없애는 새로운 방식의 인터페이스 환경을 실험하였다. 뇌파의 분석을 통하여 실시간으로 사용자의 감성 관련 반응을 반영하여 음악을 선택하여 제공하는 시스템이다. 이 논문은 개인의 감성적 반응에 의하여 상호작용하는 음악 추천 서비스인 MyMusicShuffler 시스템의 구현 내용을 설명할 것이다.

인공지능 기반 작곡 프로그램 현황 및 제언 (Artificial Intelligence Applications to Music Composition)

  • 이성훈
    • 문화기술의 융합
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    • 제4권4호
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    • pp.261-266
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    • 2018
  • 본 연구는 인공지능 기반 작곡 프로그램 현황을 살펴보고 실정을 고려한 제언을 제공하고자 한다. 인공지능 기반 작곡 프로그램은 기존의 '전문가 시스템' 방식의 알고리즘을 벗어나 심층신경망 이론의 발전 및 빅데이터 처리 기술 향상과 더불어 눈부신 성장을 보이고 있다. 이에 따라 클래식 음악과, 팝음악을 작곡하는데 있어 인공지능 기반 작곡 프로그램이 학계와 산업계에서 다양하게 제안되고 있으며, 최근 수년 사이 대중의 평가도 달라지고 있다. 다만 해당 기술 개발과 관련하여 여전한 한계점들이 분명히 존재하는 바, 대중의 인식 문제, 데이터베이스화되지 않은 가치 있는 사료들의 누락, 관련 법규의 미비, 음악적인 부분보다는 기술적 관점에서 해당 산업이 주도되는 점 등을 개선할 필요가 있겠다. 이 같은 점이 보완된다면, 인공지능 기반 기술은 국가 경쟁력 확보와 유지에 있어 중요한 역할을 해낼 것으로 보인다.

구성적 음악 창작: 컴퓨터 기반 전자적 음악 프로덕션 상에서 샘플링의 과정과 효과 (Constructive music creation: the process and effectiveness of sampling in computer-based electronic music production)

  • 한진승
    • 한국콘텐츠학회:학술대회논문집
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    • 한국콘텐츠학회 2009년도 춘계 종합학술대회 논문집
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    • pp.127-134
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    • 2009
  • 컴퓨터에서 생성되는 전자적 음악의 심미적 가치에 관한 논란 속에서도 지난 십년간 음악 기술의 발전은 음악 작곡에 있어 가상 전자 악기와 샘플러 사용의 확산을 가져왔다. 컴퓨터 기반 음악 제작 플랫폼은 현재 일부 작곡가들에게는 표준이 되었을 뿐만 아니라 중요한 음악 저작 도구가 되었다. 컴퓨터 기반 음악 제작에서의 샘플링을 활용한 작곡 과정에 있어 두 가지 중요한 부분이 있는데, 그것은 이미 녹음된 오디오 샘플을 담고 있는 상용화된 샘플 라이브러리와 이 샘플을 처리하는 음악 프로덕션 소프트웨어이다. 이 연구는 컴퓨터 음악 프로덕션 소프트웨어 상에서의 주요한 샘플링 기능을 활용한 재구성적 음악 작곡 과정과 효과를 조사하여 분석하는 것을 목적으로 한다. 이 연구의 주안점은 오디오 샘플링 정의, 음악 작곡 과정에서의 샘플링 적용 방식, 음악 프로덕션 소프트웨어의 어떤 기능이 음악적 표현에 특정하게 유용한가에 초점이 맞추어져 있으며, 전자 또는 어쿠스틱 음악인들의 음악 창작 요구에 부응하는 연구 결과가 될 것으로 기대한다.

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Automatic Music Summarization Using Vector Quantization and Segment Similarity

  • Kim, Sang-Ho;Kim, Sung-Tak;Kim, Hoi-Rin
    • The Journal of the Acoustical Society of Korea
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    • 제27권2E호
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    • pp.51-56
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    • 2008
  • In this paper, we propose an effective method for music summarization which automatically extracts a representative part of the music by using signal processing technology. Proposed method uses a vector quantization technique to extract several segments which can be regarded as the most important contents in the music. In general, there is a repetitive pattern in music, and human usually recognizes the most important or catchy tune from the repetitive pattern. Thus the repetition which is extracted using segment similarity is considered to express a music summary. The segments extracted are again combined to generate a complete music summary. Experiments show the proposed method captures the main theme of the music more effectively than conventional methods. The experimental results also show that the proposed method could be used for real-time application since the processing time in generating music summary is much faster than other methods.