Rethinking Data Augmentation in Text-to-text Paradigm

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).

Data Augmentation

Plugin Speech Enhancement: A Universal Speech Enhancement Framework Inspired by Dynamic Neural Network

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.

Data Augmentation Speech Enhancement

Harmonic gated compensation network plus for ICASSP 2022 DNS CHALLENGE

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.