Harmonizing Melody with Meta-Structure of Piano Accompaniment Figure

In this paper, a meta-structure of piano accompaniment figure (meta-structure for short) is proposed to harmonize a melodic piece of music so as to construct a multi-voice music. Here we approach melody harmonization with piano accompaniment as a machine learning task in a probabilistic framework. A series of piano accompaniment figures are collected from the massive existing sample scores and converted into a set of meta-structure. After the procedure of samples training, a model is formulated to generate a proper piano accompaniment figure for a harmonizing unit in the context. This model is flexible in harmonizing a melody with piano accompaniment. The experimental results are evaluated and discussed.     

人机交互的自动钢琴伴奏系统的研究

针对基于隐马尔科夫模型(HMM)的算法而实现的作曲系统进行改进,提出了利用人机交互式的音乐伴奏音型选择方式,实现了使不具备音乐知识的使用者也可以创作出善心悦目的乐曲。系统的给出了人机交互式创作的原理以及理论支持,通过实验证明了人机交互系统的可行性。最后邀请了三位专业作曲家对改进后的伴奏结果进行了系统评估,评估认为,计算机作曲系统可以创作出大众喜欢的音乐作品。