no code implementations • 10 Feb 2020 • Jaesung Huh, Egil Martinsson, Adrian Kim, Jung-Woo Ha
Musical onset detection can be formulated as a time-to-event (TTE) or time-since-event (TSE) prediction task by defining music as a sequence of onset events.
7 code implementations • ICLR 2019 • Hyeong-Seok Choi, Jang-Hyun Kim, Jaesung Huh, Adrian Kim, Jung-Woo Ha, Kyogu Lee
Most deep learning-based models for speech enhancement have mainly focused on estimating the magnitude of spectrogram while reusing the phase from noisy speech for reconstruction.
1 code implementation • 21 Dec 2018 • Jang-Hyun Kim, Jaejun Yoo, Sanghyuk Chun, Adrian Kim, Jung-Woo Ha
We present a hybrid framework that leverages the trade-off between temporal and frequency precision in audio representations to improve the performance of speech enhancement task.
Audio and Speech Processing Sound
no code implementations • 8 Oct 2018 • Jinwoong Kim, Minkyu Kim, Heungseok Park, Ernar Kusdavletov, Dongjun Lee, Adrian Kim, Ji-Hoon Kim, Jung-Woo Ha, Nako Sung
Many hyperparameter optimization (HyperOpt) methods assume restricted computing resources and mainly focus on enhancing performance.
no code implementations • 27 Sep 2018 • Egil Martinsson, Adrian Kim, Jaesung Huh, Jaegul Choo, Jung-Woo Ha
Predicting the time to the next event is an important task in various domains.
no code implementations • 16 Dec 2017 • Jung-Woo Ha, Adrian Kim, Chanju Kim, Jang-Yeon Park, Sunghun Kim
Music highlights are valuable contents for music services.