Search Results for author:
Found 4 papers, 1 papers with code
Scaling Unsupervised Domain Adaptation through Optimal Collaborator Selection and Lazy Discriminator Synchronization
Breakthroughs in unsupervised domain adaptation (uDA) have opened up the possibility of adapting models from a label-rich source domain to unlabeled target domains.
Libri-Adapt: A New Speech Dataset for Unsupervised Domain Adaptation
This paper introduces a new dataset, Libri-Adapt, to support unsupervised domain adaptation research on speech recognition models.
Mic2Mic: Using Cycle-Consistent Generative Adversarial Networks to Overcome Microphone Variability in Speech Systems
A major challenge in building systems that combine audio models with commodity microphones is to guarantee their accuracy and robustness in the real-world.
Multi-Step Decentralized Domain Adaptation
Despite the recent breakthroughs in unsupervised domain adaptation (uDA), no prior work has studied the challenges of applying these methods in practical machine learning scenarios.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
