Syllable-level lyrics generation from melody exploiting character-level language model

Yi Yu

Abstract:

The generation of lyrics tightly connected to
accompanying melodies involves establishing
a mapping between musical notes and syllables of lyrics. This process requires a deep
understanding of music constraints and semantic patterns at syllable-level, word-level, and
sentence-level semantic meanings. However,
pre-trained language models specifically designed at the syllable level are publicly unavailable. To solve these challenging issues, we
propose to exploit fine-tuning character-level
language models for syllable-level lyrics generation from symbolic melody. In particular,
our method endeavors to incorporate linguistic
knowledge of the language model into the beam
search process of a syllable-level Transformer
generator network. Additionally, by exploring
ChatGPT-based evaluation for generated lyrics,
along with human subjective evaluation, we
demonstrate that our approach enhances the coherence and correctness of the generated lyrics,
eliminating the need to train expensive new language models.