Hierarchical Diffusion Models for Singing Voice Neural Vocoder. (arXiv:2210.07508v1 [cs.SD])

Recent progress in deep generative models has improved the quality of neural
vocoders in speech domain. However, it remains challenging to generate
high-quality singing voice 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 …

arxiv diffusion diffusion models hierarchical neural vocoder voice