PeriodGrad: Towards Pitch-Controllable Neural Vocoder Based on a Diffusion Probabilistic Model

This paper presents a neural vocoder based on a denoising diffusion probabilistic model (DDPM) incorporating explicit periodic signals as auxiliary conditioning signals. Recently, DDPM-based neural vocoders have gained prominence as non-autoregressive models that can generate high-quality waveforms....

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Veröffentlicht in:	Proceedings of the ... IEEE International Conference on Acoustics, Speech and Signal Processing (1998) S. 12782 - 12786
Hauptverfasser:	Hono, Yukiya, Hashimoto, Kei, Nankaku, Yoshihiko, Tokuda, Keiichi
Format:	Tagungsbericht
Sprache:	Englisch Japanisch
Veröffentlicht:	IEEE 14.04.2024
Schlagworte:	Controllability diffusion probabilistic model neural vocoder pitch controllability Probabilistic logic Robustness Signal processing singing voice synthesis Speech processing Speech synthesis Training Vocoders
ISSN:	2379-190X
Online-Zugang:	Volltext
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