A Time-Series Phrase Correlation Computing System With Acoustic Signal Processing For Music Media Creation

Keiichi Tsuneyama, Yasushi Kiyoki


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 “phrases” and “three musical elements” (rhythm, melody, and harmony), which are meaningful for human recognition. By calculating the correlation between the target “target music piece” and the “typical phrase” 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.


Music Information Retrieval, Acoustic Signal Processing, Time-series Data Processing, Correlation Calculation

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DOI: 10.24003/emitter.v5i1.188


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