An Improved Supervised Speech Separation Method Based on Perceptual Weighted Deep Recurrent Neural Networks-Reference-Cited by-同舟云学术

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An Improved Supervised Speech Separation Method Based on Perceptual Weighted Deep Recurrent Neural Networks

Published:2017 Issue:2 Volume:E100.A Page:718-721
ISSN:0916-8508
Container-title:IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
language:en
Short-container-title:IEICE Trans. Fundamentals

Author:

HAN Wei¹,ZHANG Xiongwei¹,SUN Meng¹,LI Li¹,SHI Wenhua¹

Affiliation:

1. PLA University of Science and Technology

Publisher

Institute of Electronics, Information and Communications Engineers (IEICE)

Subject

Applied Mathematics,Electrical and Electronic Engineering,Computer Graphics and Computer-Aided Design,Signal Processing

Link

https://www.jstage.jst.go.jp/article/transfun/E100.A/2/E100.A_718/_pdf

Reference11 articles.

1. [1] P.C. Loizou, Speech Enhancement: Theory and Practice, CRC press, 2013.

2. [2] M. Sun, Y.N. Li, J.F. Gemmeke, and X.W. Zhang, “Speech enhancement under low SNR conditions via noise estimation using sparse and low-rank NMF with Kullback-Leibler divergence,” IEEE/ACM Trans. Audio Speech Lang. Process., vol.23, no.7, pp.1233-1242, 2015.

3. [3] M. Sun, X.W. Zhang, H.V. Hamme, and T.F. Zheng, “Unseen noise estimation using separable deep auto encoder for speech enhancement,” IEEE/ACM Trans. Audio Speech Lang. Process., vol.24, no.1, pp.93-104, 2016.

4. [4] Y. Xu, J. Du, L.R. Dai, and C.H. Lee, “A regression approach to speech enhancement based on deep neural networks,” IEEE/ACM Trans. Audio Speech Lang. Process., vol.23, no.1, pp.7-19, 2014.

5. [5] Y.X. Wang, A. Narayanan, and D.L. Wang, “On training targets for supervised speech separation,” IEEE/ACM Trans. Audio Speech Lang. Process., vol.22, no.12, pp.1849-1858, 2014.

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Error Modeling via Asymmetric Laplace Distribution for Deep Neural Network Based Single-Channel Speech Enhancement;Interspeech 2018;2018-09-02

2. A Joint Convolutional Bidirectional LSTM Framework for Facial Expression Recognition;IEICE Transactions on Information and Systems;2018

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