Change search
ReferencesLink to record
Permanent link

Direct link
Adaptive Sub band GSC Beam forming using Linear Microphone-Array for Noise Reduction/Speech Enhancement.
Blekinge Institute of Technology, School of Engineering.
2012 (English)Independent thesis Advanced level (degree of Master (Two Years))Student thesisAlternative title
Adaptive Sub band GSC Beam forming using Linear Microphone-Array for Noise Reduction/Speech Enhancement. (Swedish)
Abstract [en]

This project presents the description, design and the implementation of a 4-channel microphone array that is an adaptive sub-band generalized side lobe canceller (GSC) beam former uses for video conferencing, hands-free telephony etc, in a noisy environment for speech enhancement as well as noise suppression. The side lobe canceller evaluated with both Least Mean Square (LMS) and Normalized Least Mean Square (NLMS) adaptation. A testing structure is presented; which involves a linear 4-microphone array connected to collect the data. Tests were done using one target signal source and one noise source. In each microphone’s, data were collected via fractional time delay filtering then it is divided into sub-bands and applied GSC to each of the subsequent sub-bands. The overall Signal to Noise Ratio (SNR) improvement is determined from the main signal and noise input and output powers, with signal-only and noise-only as the input to the GSC. The NLMS algorithm significantly improves the speech quality with noise suppression levels up to 13 dB while LMS algorithm is giving up to 10 dB. All of the processing for this thesis is implemented on a computer using MATLAB and validated by considering different SNR measure under various types of blocking matrix, different step sizes, different noise locations and variable SNR with noise.

Place, publisher, year, edition, pages
2012. , 52 p.
Keyword [en]
Generalized Side lobe Canceller (GSC), Blocking matrix, Microphone array, Sub band, SNR.
National Category
Signal Processing Computer Science Telecommunications
URN: urn:nbn:se:bth-6174Local ID: diva2:833603
Mamun Ahmed E-mail: mamuncse99cuet@yahoo.comAvailable from: 2015-04-22 Created: 2012-03-20 Last updated: 2015-06-30Bibliographically approved

Open Access in DiVA

fulltext(1231 kB)210 downloads
File information
File name FULLTEXT01.pdfFile size 1231 kBChecksum SHA-512
Type fulltextMimetype application/pdf

By organisation
School of Engineering
Signal ProcessingComputer ScienceTelecommunications

Search outside of DiVA

GoogleGoogle Scholar
Total: 210 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Total: 232 hits
ReferencesLink to record
Permanent link

Direct link