3 citations · 4 across the 4 of their papers we have counts for
4 papers
TTS-by-TTS 2: Data-selective augmentation for neural speech synthesis using ranking support vector machine with variational autoencoder
Eunwoo Song, Ryuichi Yamamoto, Ohsung Kwon +6
Recent advances in synthetic speech quality have enabled us to train text-to-speech (TTS) systems by using synthetic corpora. However, merely increasing the amount of synthetic dat…
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…
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…
Speaker-adaptive neural vocoders for parametric speech synthesis systems
Eunwoo Song, Jin-Seob Kim, Kyungguen Byun +1
This paper proposes speaker-adaptive neural vocoders for parametric text-to-speech (TTS) systems. Recently proposed WaveNet-based neural vocoding systems successfully generate a ti…