Open AccessPerformance Analysis of LMS, NLMS Adaptive Algorithms for Speech Enhancement in Noisy Environment
Author(s) -
Ch. D. Umasankar*,
M. Satya Sairam
Publication year - 2020
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.d1864.029420
Subject(s) - speech enhancement , least mean squares filter , noise (video) , computer science , speech recognition , adaptive filter , mean squared error , algorithm , noise reduction , signal to noise ratio (imaging) , active noise control , signal (programming language) , mathematics , artificial intelligence , statistics , telecommunications , image (mathematics) , programming language
The speech enhancement is an important technique to remove noise from corrupted speech signal. Here several Adaptive Algorithms were proposed to improve quality of speech signal. In this paper to estimate the speech enhancement performance with variety of noise reduction algorithms using adaptive filters like LMS, NLMS. Simulations were performed on noisy data which was prepared by adding machinegun, Factory, vehicle and Traffic noise at 0dB, 5dB and 10dB SNR levels to clean speech samples The performance comparison of adaptive noise cancellation (ANC) system using LMS and NLMS algorithms was carried by means of signal to noise ratio (SNR), mean square error (MSE) and root mean square error (RMSE). Based on performance analysis, the NLMS algorithm was found to be a better optimal adaptive noise canceller for speech signal