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Found 3 papers, 3 papers with code
Improving Diffusion Models's Data-Corruption Resistance using Scheduled Pseudo-Huber Loss
Diffusion models are known to be vulnerable to outliers in training data.
Diffusion-Based Voice Conversion with Fast Maximum Likelihood Sampling Scheme
Voice conversion is a common speech synthesis task which can be solved in different ways depending on a particular real-world scenario.
Grad-TTS: A Diffusion Probabilistic Model for Text-to-Speech
Recently, denoising diffusion probabilistic models and generative score matching have shown high potential in modelling complex data distributions while stochastic calculus has provided a unified point of view on these techniques allowing for flexible inference schemes.
Ranked #3 on
Text-To-Speech Synthesis
on LJSpeech
(using extra training data)
