activity
20202022
most citedDiff-TTS: A Denoising Diffusion Model for Text-to-Speech

8 citations · 25 across the 5 of their papers we have counts for

collaborators

7 papers

cs.SD20228 cited

NANSY++: Unified Voice Synthesis with Neural Analysis and Synthesis

Hyeong-Seok Choi, Jinhyeok Yang, Juheon Lee +1

Various applications of voice synthesis have been developed independently despite the fact that they generate "voice" as output in common. In addition, most of the voice synthesis…

cs.LG20211 cited

Scheduling Optimization Techniques for Neural Network Training

Hyungjun Oh, HyeongJu Kim, Jiwon Seo

Neural network training requires a large amount of computation and thus GPUs are often used for the acceleration. While they improve the performance, GPUs are underutilized during…

eess.AS20218 cited

Diff-TTS: A Denoising Diffusion Model for Text-to-Speech

Myeonghun Jeong, Hyeongju Kim, Sung Jun Cheon +2

Although neural text-to-speech (TTS) models have attracted a lot of attention and succeeded in generating human-like speech, there is still room for improvements to its naturalness…

eess.SP20211 cited

Continuous Monitoring of Blood Pressure with Evidential Regression

Hyeongju Kim, Woo Hyun Kang, Hyeonseung Lee +1

Photoplethysmogram (PPG) signal-based blood pressure (BP) estimation is a promising candidate for modern BP measurements, as PPG signals can be easily obtained from wearable device…

cs.SD20207 cited

WaveNODE: A Continuous Normalizing Flow for Speech Synthesis

Hyeongju Kim, Hyeonseung Lee, Woo Hyun Kang +3

In recent years, various flow-based generative models have been proposed to generate high-fidelity waveforms in real-time. However, these models require either a well-trained teach…

eess.AS2020

Gated Recurrent Context: Softmax-free Attention for Online Encoder-Decoder Speech Recognition

Hyeonseung Lee, Woo Hyun Kang, Sung Jun Cheon +2

Recently, attention-based encoder-decoder (AED) models have shown state-of-the-art performance in automatic speech recognition (ASR). As the original AED models with global attenti…