1 code implementation • 8 Jan 2024 • Jayeon Yi, Junghyun Koo, Kyogu Lee
Clipping is a common nonlinear distortion that occurs whenever the input or output of an audio system exceeds the supported range.
no code implementations • 24 Aug 2023 • Yunkee Chae, Junghyun Koo, Sungho Lee, Kyogu Lee
With the proliferation of video platforms on the internet, recording musical performances by mobile devices has become commonplace.
no code implementations • 24 Jul 2023 • Junghyun Koo, Yunkee Chae, Chang-Bin Jeon, Kyogu Lee
Music source separation (MSS) faces challenges due to the limited availability of correctly-labeled individual instrument tracks.
1 code implementation • 4 Nov 2022 • Junghyun Koo, Marco A. Martínez-Ramírez, Wei-Hsiang Liao, Stefan Uhlich, Kyogu Lee, Yuki Mitsufuji
We propose an end-to-end music mixing style transfer system that converts the mixing style of an input multitrack to that of a reference song.
no code implementations • 6 Apr 2022 • Jin Woo Lee, Eungbeom Kim, Junghyun Koo, Kyogu Lee
Our study allows us to analyze which attribute of speech signals is advantageous for the CM systems.
1 code implementation • 17 Feb 2022 • Junghyun Koo, Seungryeol Paik, Kyogu Lee
Mastering is an essential step in music production, but it is also a challenging task that has to go through the hands of experienced audio engineers, where they adjust tone, space, and volume of a song.
no code implementations • 3 Mar 2021 • Junghyun Koo, Seungryeol Paik, Kyogu Lee
This method enables us to apply the reverb of the reference track to the source track to which the effect is desired.
no code implementations • 9 Sep 2020 • Junghyun Koo, Jie Hwan Lee, Jaewoo Pyo, Yujin Jo, Kyogu Lee
In this work, we exploit various multi-modal features extracted from pre-trained networks to recognize Alzheimer's Dementia using a neural network, with a small dataset provided by the ADReSS Challenge at INTERSPEECH 2020.
no code implementations • 29 Oct 2019 • Juheon Lee, Hyeong-Seok Choi, Junghyun Koo, Kyogu Lee
In this study, we define the identity of the singer with two independent concepts - timbre and singing style - and propose a multi-singer singing synthesis system that can model them separately.
Sound Audio and Speech Processing
no code implementations • 6 Aug 2019 • Juheon Lee, Hyeong-Seok Choi, Chang-Bin Jeon, Junghyun Koo, Kyogu Lee
In this paper, we propose an end-to-end Korean singing voice synthesis system from lyrics and a symbolic melody using the following three novel approaches: 1) phonetic enhancement masking, 2) local conditioning of text and pitch to the super-resolution network, and 3) conditional adversarial training.
Sound Audio and Speech Processing