most citedJDI-T: Jointly trained Duration Informed Transformer for Text-To-Speech without Explicit Alignment

18 citations · 18 across the 2 of their papers we have counts for

collaborators

2 papers

eess.AS2023

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…

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…