Hirofumi Takamori, Takayuki Nakatsuka, Satoru Fukayama, Masataka Goto, Shigeo Morishima
Audio-Based Automatic Generation of a Piano Reduction Score by Considering the Musical Structure.
MMM 2019: MultiMedia Modeling pp 169-181
This study describes a method that automatically generates a piano reduction score from the audio recordings of popular music while considering the musical structure 킹덤러쉬 프론티어 pc. The generated score comprises both right- and left-hand piano parts, which reflect the melodies, chords, and rhythms extracted from the original audio signals 도원경. Generating such a reduction score from an audio recording is challenging because automatic music transcription is still considered to be inefficient when the input contains sounds from various instruments Sandol Gothic b. Reflecting the long-term correlation structure behind similar repetitive bars is also challenging; further, previous methods have independently generated each bar Download geozebra. Our approach addresses the aforementioned issues by integrating musical analysis, especially structural analysis, with music generation. Our method extracts rhythmic features as well as melodies and chords from the input audio recording and reflects them in the score gtunes music v9 다운로드. To consider the long-term correlation between bars, we use similarity matrices, created for several acoustical features, as constraints. We further conduct a multivariate regression analysis to determine the acoustical features that represent the most valuable constraints for generating a musical structure Download the Kakao tv video. We have generated piano scores using our method and have observed that we can produce scores that differently balance between the ability to achieve rhythmic characteristics and the ability to obtain musical structures 인터스텔라.