A Hierarchical Recurrent Neural Network for Symbolic Melody Generation

Understand

In recent years, neural networks have been used to generate symbolic melodies.

• However, the long-term structure in the melody has posed great difficulty for designing a good model.
• In this paper, we present a hierarchical recurrent neural network for melody generation, which consists of three Long-Short-Term-Memory (LSTM) subnetworks working in a coarse-to-fine manner along time.
• Specifically, the three subnetworks generate bar profiles, beat profiles and notes in turn, and the output of the high-level subnetworks are fed into the low-level subnetworks, serving as guidance for generating the finer time-scale melody components in low-level subnetworks.