• The Journal of the Korea Contents Association
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• v.15 no.3
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• pp.1-10
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• 2015

Generating chord score based on melody is essential for composition and arrangement, while it is picky for amateurs who do not have harmonics knowledges. To solve this problem, we developed automatic chord score generating program, ACGP. Based on genetic algorithm, it successfully reflects diverse hormonic factors and the mood of the music. User interface was also implemented so that anyone can use the program conveniently. Additional analysis was conducted to prove the utility of ACGP.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.6
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• pp.1210-1216
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• 2003

Traditional indexing mechanism are based on the song's metadata such as the title and the composer and so on. However, these system have a major limitation that users have to know the metadata of the songs they want to retrieve. In order to solve these limitation, we proposed a rhythm extraction system that allows users to retrieve music information efficiently from a large music database using the rhythm that is defined as the parts of the music.

• Journal of IKEEE
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• v.23 no.1
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• pp.249-253
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• 2019

Most of music-transcription systems that have been commercialized operate based on audio information. However, these conventional systems have disadvantages of environmental dependency, equipment dependency, and time latency. This paper studied a vision-based music-transcription system that utilizes video information rather than audio information, which is a traditional method of music-transcription programs. Computer vision technology is widely used as a field for analyzing and applying information from equipment such as cameras. In this paper, we created a program to generate MIDI file which is electronic music notes by using smart-phone cameras to record the play of piano.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.04a
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• pp.1025-1027
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• 2015

작곡가들에게 순간 순간 떠오르는 영감을 피아노로 연주했을 때, 바로 악보화 하여 작곡에 도움을 주는 애플리케이션을 개발한다. 본 논문에서 개발한 애플리케이션은 안드로이드 환경에서 FFT(Fourier Fast Transform)이라는 주파수 측정 기술을 이용하여 계이름을 확인한 후 이를 음표와 연결시켜 악보화하는 기능을 제공한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.11a
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• pp.857-860
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• 2017

현재 초보적인 능력을 가진 악기 연주자가 접근할 수 있는 하드웨어, 소프트웨어를 사용해 악기 연주법을 연습할 수 있는 수단은 전무하다. 따라서 본 논문은 악기 연주자가 연습을 하기 위해 사용할 수 있는 음 인식과 악보 정보의 처리, LSTM을 통한 자동 악보 생성의 복합적 기능을 가진 악기 보조 시스템을 제안한다. 또한 본 시스템은 기존의 FFT와 같은 일반적인 Pitch Detection 알고리즘보다 더 우월한 음 인식 성능을 보유한 Autocorrelation 전처리를 거친 LeNet-5 Convolutional Neural Network 모델을 사용하여 음 인식 성능을 높이는 기법을 제안한다. 이 음 인식 모델은 실험 결과 기존의 음 인식 기법보다 최대 약 5.4%의 성능 증가를 이루어냈다.