Disentangled Feature Learning for Noise-Invariant Speech Enhancement
Most of the recently proposed deep learning-based speech enhancement techniques have focused on designing the neural network architectures as a black box. However, it is often beneficial to understand what kinds of hidden representations the model has learned. Since the real-world speech data are dr...
Main Authors: | , , |
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Format: | Article |
Language: | English |
Published: |
MDPI AG
2019-06-01
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Series: | Applied Sciences |
Subjects: | |
Online Access: | https://www.mdpi.com/2076-3417/9/11/2289 |