51 citations · 157 across the 17 of their papers we have counts for
20 papers
Kosp2e: Korean Speech to English Translation Corpus
Won Ik Cho, Seok Min Kim, Hyunchang Cho +1
Most speech-to-text (S2T) translation studies use English speech as a source, which makes it difficult for non-English speakers to take advantage of the S2T technologies. For some…
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…
Expressive Text-to-Speech using Style Tag
Minchan Kim, Sung Jun Cheon, Byoung Jin Choi +2
As recent text-to-speech (TTS) systems have been rapidly improved in speech quality and generation speed, many researchers now focus on a more challenging issue: expressive TTS. To…
StyleKQC: A Style-Variant Paraphrase Corpus for Korean Questions and Commands
Won Ik Cho, Sangwhan Moon, Jong In Kim +2
Paraphrasing is often performed with less concern for controlled style conversion. Especially for questions and commands, style-variant paraphrasing can be crucial in tone and mann…
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…
Unsupervised Representation Learning for Speaker Recognition via Contrastive Equilibrium Learning
Sung Hwan Mun, Woo Hyun Kang, Min Hyun Han +1
In this paper, we propose a simple but powerful unsupervised learning method for speaker recognition, namely Contrastive Equilibrium Learning (CEL), which increases the uncertainty…