51 citations · 97 across the 10 of their papers we have counts for
10 papers
Towards trustworthy phoneme boundary detection with autoregressive model and improved evaluation metric
Hyeongju Kim, Hyeong-Seok Choi
Phoneme boundary detection has been studied due to its central role in various speech applications. In this work, we point out that this task needs to be addressed not only by algo…
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…
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…
EdiTTS: Score-based Editing for Controllable Text-to-Speech
Jaesung Tae, Hyeongju Kim, Taesu Kim
We present EdiTTS, an off-the-shelf speech editing methodology based on score-based generative modeling for text-to-speech synthesis. EdiTTS allows for targeted, granular editing o…
MLP Singer: Towards Rapid Parallel Korean Singing Voice Synthesis
Jaesung Tae, Hyeongju Kim, Younggun Lee
Recent developments in deep learning have significantly improved the quality of synthesized singing voice audio. However, prominent neural singing voice synthesis systems suffer fr…
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…
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…
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…
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…
SoftFlow: Probabilistic Framework for Normalizing Flow on Manifolds
Hyeongju Kim, Hyeonseung Lee, Woo Hyun Kang +2
Flow-based generative models are composed of invertible transformations between two random variables of the same dimension. Therefore, flow-based models cannot be adequately traine…