论文标题
使用复发神经网络的节奏，和弦和旋律生成铅片
Rhythm, Chord and Melody Generation for Lead Sheets using Recurrent Neural Networks
论文作者
论文摘要
复发性神经网络产生的音乐通常缺乏方向感和连贯性。因此，我们提出了一个基于两级LSTM的铅片生成模型，其中首先产生歌曲的谐波和节奏模板，然后在第二阶段，在这些模板上生成了一系列旋律音符。主观听力测试表明，我们的方法表现优于基准，并提高了感知的音乐连贯性。
Music that is generated by recurrent neural networks often lacks a sense of direction and coherence. We therefore propose a two-stage LSTM-based model for lead sheet generation, in which the harmonic and rhythmic templates of the song are produced first, after which, in a second stage, a sequence of melody notes is generated conditioned on these templates. A subjective listening test shows that our approach outperforms the baselines and increases perceived musical coherence.
