A review of deep learning techniques for speech processing

A Mehrish, N Majumder, R Bharadwaj, R Mihalcea… - Information …, 2023 - Elsevier
The field of speech processing has undergone a transformative shift with the advent of deep
learning. The use of multiple processing layers has enabled the creation of models capable …

Deep subdomain adaptation network for image classification

Y Zhu, F Zhuang, J Wang, G Ke, J Chen… - IEEE transactions on …, 2020 - ieeexplore.ieee.org
For a target task where the labeled data are unavailable, domain adaptation can transfer a
learner from a different source domain. Previous deep domain adaptation methods mainly …

Model adaptation: Unsupervised domain adaptation without source data

R Li, Q Jiao, W Cao, HS Wong… - Proceedings of the IEEE …, 2020 - openaccess.thecvf.com
In this paper, we investigate a challenging unsupervised domain adaptation setting---
unsupervised model adaptation. We aim to explore how to rely only on unlabeled target data …

Source data-absent unsupervised domain adaptation through hypothesis transfer and labeling transfer

J Liang, D Hu, Y Wang, R He… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Unsupervised domain adaptation (UDA) aims to transfer knowledge from a related but
different well-labeled source domain to a new unlabeled target domain. Most existing UDA …