Wavefit: an Iterative and Non-Autoregressive Neural Vocoder Based on Fixed-Point Iteration

By Yuma Koizumi, Kohei Yatabe, Heiga Zen, Michiel Bacchiani. 2022

37 citations recorded by the source corpus.

Denoising diffusion probabilistic models (DDPMs) and generative adversarial networks (GANs) are popular generative models for neural vocoders. The DDPMs and GANs can be characterized by the iterative denoising framework and adversarial training, respectively. This study proposes a fast and high-quality neural vocoder called WaveFit, which integrates the essence of GANs into a DDPM-like iterative framework based on fixed-point iteration. WaveFit iteratively denoises an input signal, and trains a deep neural network (DNN) for minimizing an adversarial loss calculated from intermediate outputs at all iterations. Subjective (side-by-side) listening tests showed no statistically significant differences in naturalness between human natural speech and those synthesized by WaveFit with five iterations. Furthermore, the inference speed of WaveFit was more than 240 times faster than WaveRNN. Audio demos are available at google.github.io/df-conformer/wavefit/.

Subfields: Artificial Intelligence, Signal Processing

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Citations in the corpus

StyleTTS 2: Towards Human-Level Text-to-Speech through Style Diffusion and Adversarial Training with Large Speech Language Models (2023, methodology): “Furthermore, recent works suggest that state-of-the-art GAN-based models still perform better than diffusion models in speech synthesis [26, 33].”
Improve GAN-based Neural Vocoder using Truncated Pointwise Relativistic Least Square GAN (2022, methodology): “Another notable endeavor in this field is made by flow-based models including WaveGlow[25], FloWavenet[10], Melflow[36], WaveFlow[24], WaveFit[12] and FBWAVE[30] etc.”
A Survey on Audio Diffusion Models: Text To Speech Synthesis and Enhancement in Generative AI (2023, unknown): “Pioneering work WaveGrad [7] Code / Project DiffWave [45] Code Efficient vocoder BDDM [48] Code InferGrad [9] WaveFit [43] Project Statistical improvement DDGM [70] PriorGrad [50] Project ItôWave [125] Project SpecGrad [44] End-to-end Pioneering work WaveGrad 2 [8] Code / Project CRASH [90] Project ”