5 citations · 9 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…
Improving LPCNet-based Text-to-Speech with Linear Prediction-structured Mixture Density Network
Min-Jae Hwang, Eunwoo Song, Ryuichi Yamamoto +2
In this paper, we propose an improved LPCNet vocoder using a linear prediction (LP)-structured mixture density network (MDN). The recently proposed LPCNet vocoder has successfully…
Parameter Enhancement for MELP Speech Codec in Noisy Communication Environment
Min-Jae Hwang, Hong-Goo Kang
In this paper, we propose a deep learning (DL)-based parameter enhancement method for a mixed excitation linear prediction (MELP) speech codec in noisy communication environment. U…