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계층적 인공신경망을 이용한 구성을 갖춘 곡의 자동생성

Automatic Generation of a Configured Song with Hierarchical Artificial Neural Networks

  • 김경환 (한성대학교 전자정보공학과) ;
  • 정성훈 (한성대학교 기계전자공학부)
  • Kim, Kyung-Hwan (Department of Electronics and Information Engineering, Hansung University) ;
  • Jung, Sung Hoon (School of Mechanical and Electronic Engineering, Hansung University)
  • 투고 : 2017.07.10
  • 심사 : 2017.07.28
  • 발행 : 2017.07.31

초록

본 논문에서는 자동작곡에서 계층적 인공신경망을 이용하여 전/중/후 별로 곡의 멜로디가 전개되는 구성을 갖춘 곡을 자동으로 생성하는 방법을 제안한다. 첫 번째 계층에서는 하나의 인공신경망을 사용하여 기존의 곡을 학습시키거나 혹은 무작위 멜로디를 학습시키고 박자후처리를 하여 곡을 출력한다. 두 번째 계층에서는 첫 번째 인공신경망이 만든 멜로디를 전/중/후별로 세 개의 인공신경망에 학습한 후 곡을 출력한다. 두 번째 계층의 세 개의 인공신경망에서는 반복을 만들기 위하여 전/중/후 별로 마디구분을 이용한 반복을 적용하며 이후 박자/화성/조성후처리를 수행하여 곡을 완성한다. 실험결과 구성을 갖춘 곡이 생성됨을 확인하였다.

In this paper, we propose a method to automatically generate a configured song with melodies composed of front/middle/last parts by using hierarchical artificial neural networks in automatic composition. In the first layer, an artificial neural network is used to learn an existing song or a random melody and outputs a song after performing rhythm post-processing. In the second layer, the melody created by the artificial neural network in the first layer is learned by three artificial neural networks of front/middle/last parts in the second layer in order to make a configured song. In the artificial neural network of the second layer, we applied a method to generate repeatability using measure identity in order to make song with repeatability and after that the song is completed after rhythm, chord, tonality post-processing. It was confirmed from experiments that our proposed method produced configured songs well.

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과제정보

연구 과제 주관 기관 : 한성대학교

참고문헌

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