no code implementations • COLING 2022 • Yanan Chen, Yang Liu
As manually labelling data can be costly, some recent studies tend to augment the training data for improving the generalization power of machine learning models, known as data augmentation (DA).
no code implementations • 20 Feb 2024 • Yanan Chen, Zihao Cui, Yingying Gao, Junlan Feng, Chao Deng, Shilei Zhang
In this study, we present a novel weighting prediction approach, which explicitly learns the task relationships from downstream training information to address the core challenge of universal speech enhancement.
no code implementations • 25 Feb 2022 • Tianrui Wang, Weibin Zhu, Yingying Gao, Yanan Chen, Junlan Feng, Shilei Zhang
Therefore, we previously proposed a harmonic gated compensation network (HGCN) to predict the full harmonic locations based on the unmasked harmonics and process the result of a coarse enhancement module to recover the masked harmonics.