50 citations · 65 across the 5 of their papers we have counts for
7 papers
Improved parallel WaveGAN vocoder with perceptually weighted spectrogram loss
Eunwoo Song, Ryuichi Yamamoto, Min-Jae Hwang +3
This paper proposes a spectral-domain perceptual weighting technique for Parallel WaveGAN-based text-to-speech (TTS) systems. The recently proposed Parallel WaveGAN vocoder success…
TTS-by-TTS: TTS-driven Data Augmentation for Fast and High-Quality Speech Synthesis
Min-Jae Hwang, Ryuichi Yamamoto, Eunwoo Song +1
In this paper, we propose a text-to-speech (TTS)-driven data augmentation method for improving the quality of a non-autoregressive (AR) TTS system. Recently proposed non-AR models,…
Parallel waveform synthesis based on generative adversarial networks with voicing-aware conditional discriminators
Ryuichi Yamamoto, Eunwoo Song, Min-Jae Hwang +1
This paper proposes voicing-aware conditional discriminators for Parallel WaveGAN-based waveform synthesis systems. In this framework, we adopt a projection-based conditioning meth…
Neural text-to-speech with a modeling-by-generation excitation vocoder
Eunwoo Song, Min-Jae Hwang, Ryuichi Yamamoto +3
This paper proposes a modeling-by-generation (MbG) excitation vocoder for a neural text-to-speech (TTS) system. Recently proposed neural excitation vocoders can realize qualified w…
Parallel WaveGAN: A fast waveform generation model based on generative adversarial networks with multi-resolution spectrogram
Ryuichi Yamamoto, Eunwoo Song, Jae-Min Kim
We propose Parallel WaveGAN, a distillation-free, fast, and small-footprint waveform generation method using a generative adversarial network. In the proposed method, a non-autoreg…
Effective parameter estimation methods for an ExcitNet model in generative text-to-speech systems
Ohsung Kwon, Eunwoo Song, Jae-Min Kim +1
In this paper, we propose a high-quality generative text-to-speech (TTS) system using an effective spectrum and excitation estimation method. Our previous research verified the eff…