Neural Melody Composition from Lyrics
Abstract
In this paper, we study a novel task that learns to compose music from natural language. Given the lyrics as input, we propose a melody composition model that generates lyrics-conditional melody as well as the exact alignment between the generated melody and the given lyrics simultaneously. More specifically, we develop the melody composition model based on the sequence-to-sequence framework. It consists of two neural encoders to encode the current lyrics and the context melody respectively, and a hierarchical decoder to jointly produce musical notes and the corresponding alignment. Experimental results on lyrics-melody pairs of 18,451 pop songs demonstrate the effectiveness of our proposed methods. In addition, we apply a singing voice synthesizer software to synthesize the "singing" of the lyrics and melodies for human evaluation. Results indicate that our generated melodies are more melodious and tuneful compared with the baseline method.
Cite
@article{arxiv.1809.04318,
title = {Neural Melody Composition from Lyrics},
author = {Hangbo Bao and Shaohan Huang and Furu Wei and Lei Cui and Yu Wu and Chuanqi Tan and Songhao Piao and Ming Zhou},
journal= {arXiv preprint arXiv:1809.04318},
year = {2018}
}