Earticle

초록

영어

Noise estimation is an important part for noisy speech enhancement due to its momentous effect on the intelligibility and quality of the enhanced speech. In this paper, an effective noise estimation algorithm is presented by combining the minimum statistics estimation and Gaussian model assumption. In contrast to other methods, the proposed approach works in two steps. The noise power estimated by minimum statistics method in the first step suffers some bias which is removed by the second step of the proposed approach using Bayes theorem. As the noise estimation is refined in the second step, more accurate estimation can be obtained. The performance of the proposed approach is evaluated by objective and subjective tests under various noise environments and found to yield better results compared with conventional MS -based estimate.

목차

Abstract
 1. Introduction
 2. Minimum statistics in DCT domain
 3. Two-step Noise PSD Estimation
 4. Performance Evaluation with Speech Enhancement System
 5. Conclusions
 Acknowledgements
 References

키워드

저자

• Shifeng Ou [ Institute of Science and Technology for Opto-electronic Information, Yantai University, Yantai, 264005, China ]
• Chao Geng [ Institute of Science and Technology for Opto-electronic Information, Yantai University, Yantai, 264005, China ]
• Xianyun Wang [ Institute of Science and Technology for Opto-electronic Information, Yantai University, Yantai, 264005, China ]
• Ying Gao [ Institute of Science and Technology for Opto-electronic Information, Yantai University, Yantai, 264005, China ] Corresponding author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Signal Processing, Image Processing and Pattern Recognition

• 간기

  격월간

• pISSN

  2005-4254

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605