Search Results for author: Hyeongju Kim

Found 7 papers, 5 papers with code

EdiTTS: Score-based Editing for Controllable Text-to-Speech

1 code implementation6 Oct 2021 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.

speech editing Text-To-Speech Synthesis

Scheduling Optimization Techniques for Neural Network Training

no code implementations3 Oct 2021 Hyungjun Oh, Hyeongju Kim, Jiwon Seo

In data-parallel training, we reorder the gradient computations to maximize the overlapping of computation and parameter communication; in pipeline-parallel training, we prioritize critical gradient computations to reduce the pipeline stalls. We evaluate our optimizations with twelve neural networks including a light-weight computer vision model (MobileNet) and largeNLP models (BERT and GPT-3) with up to forty eight V100 GPUs. Our scheduling algorithms effectively improve the performance of single-GPU training as well as data- and pipeline-parallel training. Compared to the respective state of the art training systems, the throughput is substantially improved for single-GPU, data-parallel, and pipeline-parallel training.

Scheduling

MLP Singer: Towards Rapid Parallel Singing Voice Synthesis

2 code implementations arXiv 2021 Jaesung Tae, Hyeongju Kim, Younggun Lee

Recent developments in deep learning have significantly improved the quality of synthesized singing voice audio.

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

1 code implementation3 Apr 2021 Myeonghun Jeong, Hyeongju Kim, Sung Jun Cheon, Byoung Jin Choi, Nam Soo Kim

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 and architectural efficiency.

Denoising Speech Synthesis

Continuous Monitoring of Blood Pressure with Evidential Regression

no code implementations6 Feb 2021 Hyeongju Kim, Woo Hyun Kang, Hyeonseung Lee, Nam Soo Kim

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 devices in a non-invasive manner, allowing quick BP measurement.

Association regression

WaveNODE: A Continuous Normalizing Flow for Speech Synthesis

1 code implementation8 Jun 2020 Hyeongju Kim, Hyeonseung Lee, Woo Hyun Kang, Sung Jun Cheon, Byoung Jin Choi, Nam Soo Kim

In recent years, various flow-based generative models have been proposed to generate high-fidelity waveforms in real-time.

Speech Synthesis

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