所属单位：Computer School
发表刊物：Applied Intelligence
刊物所在地：https://www.springer.com/10489
摘要：Arranging and orchestration are critical aspects of music composition and production. Traditional accompaniment arranging is time-consuming and requires expertise in music theory. In this work, we utilize a deep learning model, the flow model, to generate music accompaniment including drums, guitar, bass, and strings based on the input piano melody, which can assist musicians in creating popular music. The main contributions of this paper are as follows: 1) We propose a new pianoroll representation that solves the problem of recognizing the onset of a musical note and saves space. 2) We introd
备注：The full-text of this paper can be found: https://rdcu.be/dgak2
论文类型：期刊论文
第一作者：丁凡彧
通讯作者：崔毅东
学科门类：交叉学科
文献类型：J
ISSN号：0924-669X
是否译文：否
发表时间：2023-07-06
收录刊物：SCI
发布期刊链接：https://rdcu.be/dgak2