Integrating Uncertainty Into Neural Network-Based Speech Enhancement
Author:
Affiliation:
1. Signal Processing Group, Department of Informatics, Universität Hamburg, Hamburg, Germany
2. Knowledge Technology Group, Department of Informatics, Universität Hamburg, Hamburg, Germany
Funder
German Research Foundation DFG
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Acoustics and Ultrasonics,Computer Science (miscellaneous),Computational Mathematics
Link
http://xplorestaging.ieee.org/ielx7/6570655/9970249/10094022.pdf?arnumber=10094022
Reference78 articles.
1. Noisy-target Training: A Training Strategy for DNN-based Speech Enhancement without Clean Speech
2. Ensemble learning for speech enhancement;roux;Proc IEEE Workshop Appl Signal Proc Audio Acoust,0
3. Statistical Speech Enhancement Based on Probabilistic Integration of Variational Autoencoder and Non-Negative Matrix Factorization
4. Bayesian SegNet: Model uncertainty in deep convolutional encoder-decoder architectures for scene understanding;alex;Proc Brit Mach Vis Conf,2017
5. Guided Variational Autoencoder for Speech Enhancement with a Supervised Classifier
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