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Game design to determine the balance and difficulty of the game based on the synesthesia

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An automated note generation system has been designed that improves the disadvantages of creating notes in music using BMS programs. In this paper, using FFT algorithm, the sound scale was extracted through frequency analysis of audio file and converted to color information. This was used to create automatic notes and balance the game in the rhythm game. In the case of non-complexed music such as children's songs, sound extraction was possible, but music such as K-pop, which had complex voices mixed, lacked accuracy. In this paper, the existing research on the relationship between pitch and color was objectively quantified and the system was designed to determine the balance and difficulty of the game based on the synesthesia felt by human.

Abstract

An automated note generation system has been designed that improves the disadvantages of creating notes in music using BMS programs. In this paper, using FFT algorithm, the sound scale was extracted through frequency analysis of audio file and converted to color information. This was used to create automatic notes and balance the game in the rhythm game. In the case of non-complexed music such as children's songs, sound extraction was possible, but music such as K-pop, which had complex voices mixed, lacked accuracy. In this paper, the existing research on the relationship between pitch and color was objectively quantified and the system was designed to determine the balance and difficulty of the game based on the synesthesia felt by human.

참고문헌 (16)

  1. Kenneth Peacock, "Instruments to Perform Color-Music : Two Centuries of Technological Experimentation", LEORARDO, 21(4), pp.397~406 (1998)
  2. Kenneth Peacock, "Alexander Scriabin’s Color Hearing", Music Perception Summer, 2(4), pp.483~506 (1985)
  3. Robert Plutchik, "Emotion and Life" (2003), American Psychological Association
  4. Robert Plutchik, "A psychoevolutionary theory of emotions", Social Science Information, 21(4-5), pp.529~553 (1982)
  5. Yibin Zhang, "A Study On Content-Based Music Classification", IEEE Proc. 7th International Symposium on Signal Processing and Its Applications, 2, pp.113~116 (2003)
  6. P. Knees, "Exploring Music Collections in Virtual Landscapes", IEEE multimedia, 14(3), pp.46~54 (2007)
  7. 정명범, "오디오의 파형과 FFT 분석을 이용한 대표 선율 검색", 정보과학회논문지 : 소프트웨어 및 응용, 34(12), pp.1037~1044 (2007), 한국정보과학회
  8. Jiang, D, "Music type classification by 94 spectral contrast feature", Proc. of ICME`02, 1, pp.113~116 (2002)
  9. Russell, J.A., "A Circumplex Modelof Affect", Journal of Personality and Social Psychology, 39, pp.1160~1178 (1980)
  10. GH Kim, "Sound Color Harmonism" (2003), impress

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