Deep Attention-Based Alignment Network for Melody Generation from Incomplete Lyrics
Abstract
We propose a deep attention-based alignment network, which aims to automatically predict lyrics and melody with given incomplete lyrics as input in a way similar to the music creation of humans. Most importantly, a deep neural lyrics-to-melody net is trained in an encoder-decoder way to predict possible pairs of lyrics-melody when given incomplete lyrics (few keywords). The attention mechanism is exploited to align the predicted lyrics with the melody during the lyrics-to-melody generation. The qualitative and quantitative evaluation metrics reveal that the proposed method is indeed capable of generating proper lyrics and corresponding melody for composing new songs given a piece of incomplete seed lyrics.
Cite
@article{arxiv.2301.10015,
title = {Deep Attention-Based Alignment Network for Melody Generation from Incomplete Lyrics},
author = {Gurunath Reddy M and Zhe Zhang and Yi Yu and Florian Harscoet and Simon Canales and Suhua Tang},
journal= {arXiv preprint arXiv:2301.10015},
year = {2023}
}
Comments
arXiv admin note: substantial text overlap with arXiv:2011.06380