EconPapers    
Economics at your fingertips  
 

Performance Improvement of Multi-Channel Speech Enhancement Using Modified Intelligent Kalman Filtering Algorithm

Tusar Kanti Dash and Sandeep Singh Solanki
Additional contact information
Tusar Kanti Dash: Birla Institute of Technology, Department of Electronics and Communication Engineering
Sandeep Singh Solanki: Birla Institute of Technology, Department of Electronics and Communication Engineering

A chapter in New Trends in Computational Vision and Bio-inspired Computing, 2020, pp 979-983 from Springer

Abstract: Abstract In this paper, we propose a modified multichannel Kalman speech enhancement algorithm for the enhancement of noisy signal from the effect of colored noise. Compared with other multichannel speech enhancement algorithms, the projected algorithm requires lower computational resources with satisfactory noise reduction and lower signal distortion.

Keywords: Speech enhancement; Kalman Filter (search for similar items in EconPapers)
Date: 2020
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-41862-5_99

Ordering information: This item can be ordered from
http://www.springer.com/9783030418625

DOI: 10.1007/978-3-030-41862-5_99

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2026-05-22
Handle: RePEc:spr:sprchp:978-3-030-41862-5_99