1 code implementation • 14 Feb 2020 • Sunwoo Kim, Haici Yang, Minje Kim
Speech enhancement tasks have seen significant improvements with the advance of deep learning technology, but with the cost of increased computational complexity.
no code implementations • 3 Jun 2020 • Katy Börner, Olga Scrivner, Leonard E. Cross, Michael Gallant, Shutian Ma, Adam S. Martin, Elizabeth Record, Haici Yang, Jonathan M. Dilger
Understanding the emergence, co-evolution, and convergence of science and technology (S&T) areas offers competitive intelligence for researchers, managers, policy makers, and others.
no code implementations • 28 Jul 2021 • Haici Yang, Shivani Firodiya, Nicholas J. Bryan, Minje Kim
In this work, we learn to remix music directly by re-purposing Conv-TasNet, a well-known source separation model, into two neural remixing architectures.
no code implementations • 22 Mar 2022 • Haici Yang, Sanna Wager, Spencer Russell, Mike Luo, Minje Kim, Wontak Kim
In the stereo-to-multichannel upmixing problem for music, one of the main tasks is to set the directionality of the instrument sources in the multichannel rendering results.
no code implementations • 4 Nov 2022 • Haici Yang, Wootaek Lim, Minje Kim
Low and ultra-low-bitrate neural speech coding achieves unprecedented coding gain by generating speech signals from compact speech features.
no code implementations • 14 Nov 2023 • Haici Yang, Inseon Jang, Minje Kim
In low-bitrate speech coding, end-to-end speech coding networks aim to learn compact yet expressive features and a powerful decoder in a single network.