  Computational aesthetics evaluation has made great achievements in the field
of visual arts, but the research work on music still needs to be explored.
Although the existing work of music generation is very substantial, the quality
of music score generated by AI is relatively poor compared with that created by
human composers. The music scores created by AI are usually monotonous and
devoid of emotion. Based on Birkhoff's aesthetic measure, this paper proposes
an objective quantitative evaluation method for homophony music score aesthetic
quality assessment. The main contributions of our work are as follows: first,
we put forward a homophony music score aesthetic model to objectively evaluate
the quality of music score as a baseline model; second, we put forward eight
basic music features and four music aesthetic features.
