Transfer Learning Algorithm for Enhancing the Unlabeled Speech

Transfer Learning Algorithm for Enhancing the Unlabeled Speech

To improve the generalization ability of speech enhancement algorithms for unlabeled noisy speech, a speech enhancement transfer learning model based on the feature-attention multi-kernel maximum mean discrepancy (FA-MK-MMD) is proposed. To obtain a representation of the shared subspace (the part re...

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Bibliographic Details
Main Authors: Ruiyu Liang, Zhenlin Liang, Jiaming Cheng, Yue Xie, Qingyun Wang
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Transfer learning
speech enhancement
maximum mean discrepancy
attention mechanism
Online Access:https://ieeexplore.ieee.org/document/8960349/

Internet

https://ieeexplore.ieee.org/document/8960349/

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