scholarly journals Fast converging iterative kalman filtering for speech enhancement using long and overlapped tapered windows with large side lobe attenuation

2010 ◽  
Author(s):  
Stephen So ◽  
Kuldip K. Paliwal
Keyword(s):  
Speech Enhancement ◽  
Kalman Filtering ◽  
Side Lobe ◽  
Large Side

scholarly journals Comparison of LMS and NLMS algorithm with the using of 4 Linear Microphone Array for Speech Enhancement.

2017 ◽  
Vol 2 (4) ◽  
pp. 15
Author(s):  
Mamun Ahmed ◽  
Nasimul Hyder Maruf Bhuyan
Keyword(s):  
Speech Enhancement ◽  
Noise Suppression ◽  
Signal To Noise Ratio ◽  
Microphone Array ◽  
Side Lobe ◽  
Lms Algorithm ◽  
Least Mean Square ◽  
Noise Sources ◽  
Whole Process ◽  
Nlms Algorithm

In this paper, we have presented the design, implementation and comparison result of Least Mean Square (LMS) algorithm and Normalized LMS (NLMS) algorithm using a 4 channel microphone array for noise reduction as well as speech enhancement. Adaptive sub band Generalized Side lobe Canceller (GSC) beam former has been used for experiment and analysis. Tested results were done by using one speech signal and a small number of noise sources. The side lobe canceller was evaluated with the adaptation of LMS and NLMS. The overall development of Signal to Noise Ratio (SNR) has been determined from the input and output powers of signal and noise, with signal only as input and noise, as input to the GSC. The NLMS algorithm considerably improves speech quality with noise suppression levels of up to 13 dB, while the LMS algorithm is giving up to 10 dB. In different ways of SNR measure was under various types of blocking matrix, step sizes and various noise locations. The whole process will be used for hands-free telephony, video conferencing etc. in a noisy environment.

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