25 citations · 47 across the 3 of their papers we have counts for
3 papers
eess.AS2021★ 4 cited
UnivNet: A Neural Vocoder with Multi-Resolution Spectrogram Discriminators for High-Fidelity Waveform Generation
Won Jang, Dan Lim, Jaesam Yoon +2
Most neural vocoders employ band-limited mel-spectrograms to generate waveforms. If full-band spectral features are used as the input, the vocoder can be provided with as much acou…
eess.AS2020★ 25 cited
Universal MelGAN: A Robust Neural Vocoder for High-Fidelity Waveform Generation in Multiple Domains
Won Jang, Dan Lim, Jaesam Yoon
We propose Universal MelGAN, a vocoder that synthesizes high-fidelity speech in multiple domains. To preserve sound quality when the MelGAN-based structure is trained with a datase…
eess.AS2020★ 18 cited
JDI-T: Jointly trained Duration Informed Transformer for Text-To-Speech without Explicit Alignment
Dan Lim, Won Jang, Gyeonghwan O +3
We propose Jointly trained Duration Informed Transformer (JDI-T), a feed-forward Transformer with a duration predictor jointly trained without explicit alignments in order to gener…