SPEECH ENHANCEMENT BASED ON LABEL CONSISTENT K-SVD UNDER NOISY ENVIRONMENT

DOI

10.2991/mmebc-16.2016.113How to use a DOI?

Keywords

Speech enhancement, sparse representations, K-SVD, Label Consistent K-SVD(LCKSVD).

Abstract

The sparse algorithm for sparse enhancement is more and more popular issues, recently. In previous research, the sparse algorithm for sparse enhancement will spend much time, so we propose LC K-SVD(Label Consistent K-SVD) to reduce spending time. We focus on the White Gaussian Noise. The experiments show that denoising performance of our proposed method is very closed to sparse algorithm in SNR, LLR, SNRseg and PESQ, even better then it. Our method only need half time then sparse algorithm.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

TY  - CONF
AU  - Ching-Tang Hsieh
AU  - Cheng-Yuan Chiang
AU  - Ting-Wen Chen
PY  - 2016/06
DA  - 2016/06
TI  - SPEECH ENHANCEMENT BASED ON LABEL CONSISTENT K-SVD UNDER NOISY ENVIRONMENT
BT  - Proceedings of the 2016 6th International Conference on Machinery, Materials, Environment, Biotechnology and Computer
PB  - Atlantis Press
SP  - 524
EP  - 528
SN  - 2352-5401
UR  - https://doi.org/10.2991/mmebc-16.2016.113
DO  - 10.2991/mmebc-16.2016.113
ID  - Hsieh2016/06
ER  -