Liu, Hao MinHao MinLiuYI-HSUAN YANG2023-10-122023-10-122018-07-029781538668047https://scholars.lib.ntu.edu.tw/handle/123456789/636060Research on automatic music generation has seen great progress due to the development of deep neural networks. However, the generation of multi-instrument music of arbitrary genres still remains a challenge. Existing research either works on lead sheets or multi-track piano-rolls found in MIDIs, but both musical notations have their limits. In this work, we propose a new task called lead sheet arrangement to avoid such limits. A new recurrent convolutional generative model for the task is proposed, along with three new symbolic-domain harmonic features to facilitate learning from unpaired lead sheets and MIDIs. Our model can generate lead sheets and their arrangements of eight-bar long. Source code and audio samples of the generated result can be found at the project webpage: https://liuhaumin. github.io/LeadsheetArrangement.Conditional generative adversarial network | Lead sheet arrangement | Multi-track polyphonic music generationconference paper10.1109/ICMLA.2018.001142-s2.0-85062220598https://api.elsevier.com/content/abstract/scopus_id/85062220598