Open AccessReduction of Impulsive Noise from Speech and Audio Signals by using Sd Rom Algorithm
Author(s) -
G. Manmadha Rao,
Raidu Babu D.N,
Krishna Kanth P.S.L,
B Vinay,
V S Nikhil
Publication year - 2021
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.a5943.0510121
Subject(s) - impulse noise , speech recognition , impulse (physics) , noise (video) , computer science , noise reduction , background noise , gradient noise , audio signal , value noise , noise measurement , signal to noise ratio (imaging) , noise floor , algorithm , mathematics , speech coding , artificial intelligence , physics , telecommunications , pixel , quantum mechanics , image (mathematics)
Removal of noise is the heart for speech and audio signal processing. Impulse noise is one of the most important noise which corrupts different parts in speech and audio signals. To remove this type of noise from speech and audio signals the technique proposed in this work is signal dependent rank order mean (SD-ROM) method in recursive version. This technique is used to replace the impulse noise samples based on the neighbouring samples. It detects the impulse noise samples based on the rank ordered differences with threshold values. This technique doesn’t change the features and tonal quality of signal. Rank ordered differences is used for detecting the impulse noise samples in speech and audio signals. Once the sample is detected as corrupted sample, that sample is replaced with rank ordered mean value and this rank ordered mean value depends on the sliding window size and neighbouring samples. This technique shows good results in terms of signal to noise ratio (SNR) and peak signal to noise ratio (PSNR) when compared with other techniques. It mainly used for removal of impulse noises from speech and audio signals.