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eess.AS2023
LC4SV: A Denoising Framework Learning to Compensate for Unseen Speaker Verification Models
Chi-Chang Lee, Hong-Wei Chen, Chu-Song Chen +3
The performance of speaker verification (SV) models may drop dramatically in noisy environments. A speech enhancement (SE) module can be used as a front-end strategy. However, exis…
eess.AS2020★ 1 cited
SERIL: Noise Adaptive Speech Enhancement using Regularization-based Incremental Learning
Chi-Chang Lee, Yu-Chen Lin, Hsuan-Tien Lin +2
Numerous noise adaptation techniques have been proposed to fine-tune deep-learning models in speech enhancement (SE) for mismatched noise environments. Nevertheless, adaptation to…