A Time-Series Phrase Correlation Computing System With Acoustic Signal Processing For Music Media Creation
This paper presents a system that analyzes the time-series impression change in the acoustic signal by a unit of music phrase. The aim is to support the music creation using a computer (computer music) by bringing out composers' potentially existing knowledge and skills. Our goal is to realize the cross-genre/cross-cultural music creation. Our system realizes the automatic extraction of musical features from acoustic signals by dividing and decomposing them into â€œphrasesâ€ and â€œthree musical elementsâ€ (rhythm, melody, and harmony), which are meaningful for human recognition. By calculating the correlation between the target â€œtarget music pieceâ€ and the â€œtypical phraseâ€ in each musical genre, composers are able to grasp the time-series impression change of music media by the unit of music phrase. The system leads to a new creative and efficient environment for cross-genre/cross-cultural music creation based on the potentially existing knowledge on the music phrase and structure.
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