Hierarchical Diffusion Models for Singing Voice Neural Vocoder. (arXiv:2210.07508v2 [cs.SD] UPDATED)

Recent progress in deep generative models has improved the quality of neural
vocoders in speech domain. However, generating a high-quality singing voice
remains challenging due to a wider variety of musical expressions in pitch,
loudness, and pronunciations. In this work, we propose a hierarchical diffusion
model for singing voice neural vocoders. The proposed method consists of
multiple diffusion models operating in different sampling rates; the model at
the lowest sampling rate focuses on generating accurate low-frequency
components such as pitch, …

arxiv diffusion diffusion models hierarchical neural vocoder voice