• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.725-732
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• 2009

Thanks to the development of the Internet, people can easily access a vast amount of music. This brings attention to application systems such as a melody-based music search service or music recommendation service. Extracting melodies from music is a crucial process to provide such services. This paper introduces a novel algorithm that can extract melodies from piano music. Since piano can produce polyphonic music, we expect that by studying melody extraction from piano music, we can help extract melodies from general polyphonic music.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.12
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• pp.923-927
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• 2009

The recent growth of a digital music market induces increasing demands for music searching and recommendation services. In order to improve the performance of music-based application services, the process of extracting melodies from polyphonic music is essential. In this paper, we propose a method to extract melodies from piano solo music which is highly polyphonic and has a wide pitch range. We categorize piano music into three classes taking into account the characteristics of music, and extract melodies according to each class. The performance evaluation for the implemented system showed that our method works successfully on a variety of piano solo music.

• Journal of Music and Human Behavior
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• v.2 no.2
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• pp.1-14
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• 2005

This research was to study the behavior of listening music, music preference, meaning and role of music. The interviewees were 158 male/female students of high school in second level. This research had a interview which is composed with 7 multiple choice-questions and 1 short answer-question. In result, in the question of 'The average time of listening music', the most students(64, 41.8%) answered '1~2hours', the secondary, '2~3hours' which was 32.(20.9%) In the next question, 'The preference of music genre', 87students(56.8%) answered 'Korean pop and rock', 'American pop' was 11.1% each. Regarding 'The favorite mood of music', 50.3% of students answered 'Mellow songs, 24.8% of students answered 'Jaunty songs'. Regarding 'The social factor of listening music', more than half students(56.7%) agreed that friends or something like that may affect their music preference. Likewise, 51.6% agreed that their temper or character may affect their music preference. They answered that they enjoy the music usually when they take a rest(30.1%), when in moving(24.3%). Lastly, it said 'The meaning of music' is mostly 'Getting rid of stress and Refresh'(25.1%). And 'Calmness', 'Comfort' was 21.8%. The music especially to students means 'Emotional exit'. The music which can enable them to express their feelings is related with feeling and emotion deeply. And emotional factors like stress, depression, anxiety becomes the main reason of accepting the music meaningfully. In conclusion, This research says that they experience positive feelings and express emotions through music which enables them to understand fully their feelings and emotions.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.11a
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• pp.299-300
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• 2009

본 시스템은 개인이 가지고 있는 음악의 선호에 따라 다음 번에 재생 할 음악 목록을 구성하는 것이 목적이다. 여기서 음악의 선호는 사용자가 음악을 끝까지 들었는지 혹은 음악을 끝까지 듣지 않고 다음 곡으로 넘겼는지 여부에 따라 판단된다. 또한 이 선호에 대한 누적 평가 값에 한계치를 두고 누적 평가 값과 최근 평가 값을 합산함으로써 변화하는 사용자의 취향에 맞추어 재생 목록을 구성할 수 있다. 실험을 통해 새로운 목록을 구성 할수록 평균적인 사용자의 최근 선호도에 따라 재생 목록이 구성됨을 알 수 있었다.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06a
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• pp.259-262
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• 2011

최근 들어 소리의 세기나 하모니, 템포, 리듬 등의 다양한 음악 신호 특성을 기반으로 한 음악 무드 분류에 대한 연구가 활발하게 진행되고 있다. 본 논문에서는 음악 무드 분류의 정확도를 높이기 위하여 음악 신호 특성과 더불어 노래 가사와 소셜 네트워크 상에서의 사용자 평가 등을 함께 고려하는 멀티 모달 음악 무드 분류 기법을 제안한다. 이를 위해, 우선 음악 신호 특성에 대해 퍼지 추론 기반의 음악 무드 추출 기법을 적용하여 다수의 가능한 음악 무드를 추출한다. 다음으로 음악 가사에 대해 TF-IDF 기법을 적용하여 대표 감정 키워드를 추출하고 학습시킨 가사 무드 분류기를 사용하여 가사 음악 무드를 추출한다. 마지막으로 소셜 네트워크 상에서의 사용자 태그 등 사용자 피드백을 통한 음악 무드를 추출한다. 특정 음악에 대해 이러한 다양한 경로를 통한 음악 무드를 교차 분석하여 최종적으로 음악 무드를 결정한다. 음악 분류를 기반한 자동 음악 추천을 수행하는 사용자 만족도 평가 실험을 통해서 제안하는 기법의 효율성을 검증한다.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06c
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• pp.41-44
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• 2011

본 연구는 현재 사용자가 청취한 음악과 청취한 순서를 기반으로 다음에 사용할 아이템을 추천하는 문제를 다룬다. 우리가 제시하는 모델은 아이템 사용 로그를 기반으로 하며, 정보검색에서 많이 사용하는 N-gram모델을 사용하여 아이템의 순서열을 추출한 후 다음에 올 확률이 높은 아이템을 학습한다. 그리고 사용자가 현재 선택한 아이템의 순서열을 기반으로 다음에 가장 들을 확률이 높은 아이템을 추천한다. 또 실 세계 데이터를 기반으로 실험하여 협업적 필터링 방식과 성능을 비교한다.

• Journal of Music and Human Behavior
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• v.3 no.2
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• pp.15-28
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• 2006

Music plays significant roles in the process of human development. The requirement in each process of development can be encouraged by children's participating in various musical activity and so the musical circumstance can make an important factor. Acknowledging that, there were some attempts to use music as a means of treatment or education for children. The subjects of clinic studies in music therapy, especially in Korea, have mainly been children with delay or disability in development. The purpose of this article is focused on collecting and analyzing articles which are written about children who are the main subjects of clinic studies. By collecting and analyzing those articles, the tendency of domestic studies about music therapy concerned with children can be widely examined. Ninety thesis about music therapy related with normal and disabled children have been collected and analyzed considering the subjects, methods, fields of the studies and musical intervention. The conclusions are the same with followings. First, considering the subjects, the studies on children with disabilities are more than normal children and the studies on autistic children occupy the largest portion of them Recently the studies on normal children have been increased as well as the studies on children with disability. Second, for the methods1 experimental studies have been performed more widely than descriptive studies. Third, considering the fields of development, the studies on the social field occupies the largest part of all and they are followed by emotion, language and communication, cognition in turn. Last, in case of musical intervention, it is clear that musical intervention is more used as forms of singing songs and playing instruments than special skills of music. Through this article, the achievements and shortcomings in this territory could be possibly shown at the same time. Moreover, the direction which it has to move toward could be shown.

• Journal of Music and Human Behavior
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• v.15 no.1
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• pp.1-23
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• 2018

Recently, there has been a growing focus on the concerns pre-service teachers have as they move through different stages of their teacher preparation programs. Accordingly, the purpose of this study was to investigate pre-service secondary music teachers' concerns about music teaching and learning. The specific research questions were as follows: (a) What concerns are most common among participants? (b) What are differences in the concerns of pre-service secondary music teachers based on their stage of teacher preparation? (c) What are differences in the concerns of pre-service secondary music teachers based on their previous teaching experiences? A survey was distributed to pre-service secondary music teachers in a university in Seoul, and responses from a total of 93 participants were included in the final analysis. Data analysis indicated that pre-service music teachers experienced more concerns related to teaching tasks and student impact than themselves. Also, as participants progressed through their teacher preparation programs, self concerns decreased while task concerns and student impact concerns increased. Pre-service secondary music teachers who had previously taught in a school had fewer concerns than participants with no teaching experience. Suggestions for how teacher preparation programs can address the concerns of pre-service secondary music teachers are offered.

• Journal of Music and Human Behavior
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• v.12 no.2
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• pp.61-77
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• 2015

The purpose of this study was to investigate music therapists'use and perception of computer-based music technology. Questionnaires were distributed either electronically or in-person to 367 music therapists with credentials. Of the 367 initially distributed questionnaires, 101 were returned and 61 were analyzed after excluding 40 incomplete responses. The survey was comprised of two sections: the use of music technology and perceived importance of music technology in music therapy practice. The results showed that 65.6% of the respondents had used music technology in their clinical practice. The most frequently used type of music technology was Finale, followed by Garage band, and Cubase. With regard to the areas where music technology was used, it was implemented primarily for adolescents for musical or emotional goals, and was applied most frequently as a musical resource. In addition, most respondents showed a positive attitude toward music technology and added that they would need to be trained to use music technology for their clinical practice. These results provide practical information on how music therapists use and perceive computer-based music technology, and its implication for music therapy clinical practice.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.533-536
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• 2015

Mobile music market is growing. However, services what are applied recently are inaccurate to recommend music that a user is worth to prefer. So, this paper suggests music recommend system. This system recommend music that users prefer analyzing music information and user's musical propensity and using collaborative filtering. This system classify genre and extract factors what can be get using STFT's ZCR, Spectral roll-off, Spectral flux. So similar musics are clustered by these factors. And then, after divide mood of music's lyric, it finally recommend music automatically using collaborative filtering.