25 citations · 49 across the 6 of their papers we have counts for
6 papers
FastFit: Towards Real-Time Iterative Neural Vocoder by Replacing U-Net Encoder With Multiple STFTs
Won Jang, Dan Lim, Heayoung Park
This paper presents FastFit, a novel neural vocoder architecture that replaces the U-Net encoder with multiple short-time Fourier transforms (STFTs) to achieve faster generation ra…
JETS: Jointly Training FastSpeech2 and HiFi-GAN for End to End Text to Speech
Dan Lim, Sunghee Jung, Eesung Kim
In neural text-to-speech (TTS), two-stage system or a cascade of separately learned models have shown synthesis quality close to human speech. For example, FastSpeech2 transforms a…
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…
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…
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…
Convolutional Attention-based Seq2Seq Neural Network for End-to-End ASR
Dan Lim
This thesis introduces the sequence to sequence model with Luong's attention mechanism for end-to-end ASR. It also describes various neural network algorithms including Batch norma…