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Yu Liao

2 accepted papers

2025

Leveraging Out-of-Domain Noise for Unsupervised Domain Adaptation in Speech Enhancement

ICASSP 2025accepted

When there’s a mismatch between the training and test domains, supervised speech enhancement (SE) models trained on synthetic paired noisy-clean data often struggle in real-world scenarios, highlighting the industry’s strong demand for unsupervised training and domain adaptation methods. In this stu…

Cited by 0SourceScholar
2024

GeneFormer: Learned Gene Compression using Transformer-Based Context Modeling

ICASSP 2024accepted

The development of gene sequencing technology sparks an explosive growth of gene data. Thus, the storage of gene data has become an important issue. Recently, researchers begin to investigate deep learning-based gene data compression, which outperforms general traditional methods. In this paper, we…

Cited by 0SourceScholar