Unsupervised Source Free Domain Adaptation by Batch Normalization for Speaker Verification
Abstract
References
Index Terms
- Unsupervised Source Free Domain Adaptation by Batch Normalization for Speaker Verification
Recommendations
Domain Adaptation for Speaker Verification Based on Self-supervised Learning with Adversarial Training
MultiMedia ModelingAbstractSpeaker verification models trained on a single domain have difficulty keeping performance on new domain data. Adversarial training maps different domain data to the same subspace to handle this problem. However, adversarial training only uses ...
Reducing bias to source samples for unsupervised domain adaptation
AbstractUnsupervised Domain Adaptation (UDA) makes predictions for the target domain data while labels are only available in the source domain. Lots of works in UDA focus on finding a common representation of the two domains via domain alignment, ...
Highlights- A novel method named RBDA is proposed for domain adaptation.
- RBDA focuses on reducing the classifier’s bias to source samples.
- Comprehensive experiments demonstrate the effectiveness of RBDA.
Source Data-free Unsupervised Domain Adaptation for Semantic Segmentation
MM '21: Proceedings of the 29th ACM International Conference on MultimediaDeep\footnote learning-based semantic segmentation methods require a huge amount of training images with pixel-level annotations. Unsupervised domain adaptation (UDA) for semantic segmentation enables transferring knowledge learned from the synthetic ...
Comments
Information & Contributors
Information
Published In
![cover image ACM Other conferences](/cms/asset/dafccbe7-508b-4229-8554-9c17c3c75090/3704323.cover.jpg)
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Check for updates
Author Tags
Qualifiers
- Research-article
Funding Sources
- National Natural Science Foundation of China
- R&D Program of Beijing Municipal Education Commission
Conference
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 7Total Downloads
- Downloads (Last 12 months)7
- Downloads (Last 6 weeks)7
Other Metrics
Citations
View Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in