4 papers
WaveNeXt 2: ConvNeXt-Based Fast Neural Vocoders With Residual Denoising and Sub-Modeling for GAN and Diffusion Models
Wangzixi Zhou, Takuma Okamoto, Yamato Ohtani +2
Most neural vocoders are limited to one type: either GAN or diffusion-based. While state-of-the-art models like Vocos and WaveNeXt use powerful ConvNeXt-based generators, they have…
Layer-wise Analysis for Quality of Multilingual Synthesized Speech
Erica Cooper, Takuma Okamoto, Yamato Ohtani +2
While supervised quality predictors for synthesized speech have demonstrated strong correlations with human ratings, their requirement for in-domain labeled training data hinders t…
A Cyclical Approach to Synthetic and Natural Speech Mismatch Refinement of Neural Post-filter for Low-cost Text-to-speech System
Yi-Chiao Wu, Patrick Lumban Tobing, Kazuki Yasuhara +3
Neural-based text-to-speech (TTS) systems achieve very high-fidelity speech generation because of the rapid neural network developments. However, the huge labeled corpus and high c…
A Cyclical Post-filtering Approach to Mismatch Refinement of Neural Vocoder for Text-to-speech Systems
Yi-Chiao Wu, Patrick Lumban Tobing, Kazuki Yasuhara +3
Recently, the effectiveness of text-to-speech (TTS) systems combined with neural vocoders to generate high-fidelity speech has been shown. However, collecting the required training…