313 citations · 376 across the 17 of their papers we have counts for
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eess.AS2021★ 1 cited
BLOOM-Net: Blockwise Optimization for Masking Networks Toward Scalable and Efficient Speech Enhancement
Sunwoo Kim, Minje Kim
In this paper, we present a blockwise optimization method for masking-based networks (BLOOM-Net) for training scalable speech enhancement networks. Here, we design our network with…
eess.AS2021★ 4 cited
Test-Time Adaptation Toward Personalized Speech Enhancement: Zero-Shot Learning with Knowledge Distillation
Sunwoo Kim, Minje Kim
In realistic speech enhancement settings for end-user devices, we often encounter only a few speakers and noise types that tend to reoccur in the specific acoustic environment. We…
eess.AS2021★ 2 cited
Personalized Speech Enhancement through Self-Supervised Data Augmentation and Purification
Aswin Sivaraman, Sunwoo Kim, Minje Kim
Training personalized speech enhancement models is innately a no-shot learning problem due to privacy constraints and limited access to noise-free speech from the target user. If t…