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pro vyhledávání: '"Jung, SoonYoung"'
In this report, we present our award-winning solutions for the Music Demixing Track of Sound Demixing Challenge 2023. First, we propose TFC-TDF-UNet v3, a time-efficient music source separation model that achieves state-of-the-art results on the MUSD
Externí odkaz:
http://arxiv.org/abs/2306.09382
In recent years, neural network based methods have been proposed as a method that cangenerate representations from music, but they are not human readable and hardly analyzable oreditable by a human. To address this issue, we propose a novel method to
Externí odkaz:
http://arxiv.org/abs/2111.13321
Conditioned source separations have attracted significant attention because of their flexibility, applicability and extensionality. Their performance was usually inferior to the existing approaches, such as the single source separation model. However
Externí odkaz:
http://arxiv.org/abs/2111.12516
Recently, many methods based on deep learning have been proposed for music source separation. Some state-of-the-art methods have shown that stacking many layers with many skip connections improve the SDR performance. Although such a deep and complex
Externí odkaz:
http://arxiv.org/abs/2111.12203
This paper proposes a neural network that performs audio transformations to user-specified sources (e.g., vocals) of a given audio track according to a given description while preserving other sources not mentioned in the description. Audio Manipulat
Externí odkaz:
http://arxiv.org/abs/2104.13553
Recent deep-learning approaches have shown that Frequency Transformation (FT) blocks can significantly improve spectrogram-based single-source separation models by capturing frequency patterns. The goal of this paper is to extend the FT block to fit
Externí odkaz:
http://arxiv.org/abs/2010.11631
Investigating U-Nets with various Intermediate Blocks for Spectrogram-based Singing Voice Separation
Singing Voice Separation (SVS) tries to separate singing voice from a given mixed musical signal. Recently, many U-Net-based models have been proposed for the SVS task, but there were no existing works that evaluate and compare various types of inter
Externí odkaz:
http://arxiv.org/abs/1912.02591
Autor:
Jung, Soonyoung, Nandi, Dip K., Yeo, Seungmin, Kim, Hyungjun, Jang, Yujin, Bae, Jong-Seong, Hong, Tae Eun, Kim, Soo-Hyun
Publikováno v:
In Surface & Coatings Technology 15 March 2018 337:404-410
Autor:
Chae, Jeongmin, Jung, Younghee, Lee, Taemin, Jung, Soonyoung, Huh, Chan, Kim, Gilhan, Kim, Hyeoncheol, Oh, Heungbum
Publikováno v:
In Journal of Biomedical Informatics February 2014 47:139-152
Akademický článek
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