Adaptive Filtering with Averaging in Noise Cancellation for Voice and Speech Recognition (original) (raw)

Review of Noise Cancellation of Speech Signal by Using Adaptive Filtering with RLS Algorithm

2015

In communication system, if statistical property of the signal is known then we are use a fixed filter but when the property of the signal is unknown we used adaptive filter. Adaptive filter is one of the most important areas in DSP to remove background noise. In this paper, we describe the noise cancelling using recursive least square (RLS) algorithm to remove the noise from input signal. The RLS adaptive filter uses as a reference signal on the input port and desired signal on the desired port to automatically match the filter response in noise filter block. The filtered noise should be completely subtracted from the noise signal of the input speech signal and noise input signal and the error signal should contain only the original signal.

Noise Cancellation Using Adaptive Filters of Speech Signal by RLS Algorithm in Matlab

2015

In wireless communication, if the property of signal are given, fixed filter are used by us.. but when the property of signals are unknown then we require to adjust the filter, this type of filter is called adaptive filter. It is use for remove the background noise. Here, in this paper we are introducing a new method for noise cancellation through RLS algorithm in matlab. It is more efficiencally and effectively from the other method of noise cancellation. The update filter coefficient are auto considered, so this method is very fast response and find estimated error and getting the original noise. Here we are using a speech signal as a input signal that should being contained many type of noise.

Adaptive Noise Cancellation for Speech Processing in Real Time Environment

2013

The most common problem in speech processing is the interference noise in speech signals. Interference can come from acoustical sources such as ventilation equipment, traffic crowds and commonly reverberation and echoes. The basic adaptive algorithm is the LMS algorithm but its’ major drawback is the excess mean square error increase linearly with the desired signal power. We proposed an algorithm for adaptive noise cancellation using normalized differential least mean square NDLMS algorithm in real time environment. In this paper NDLMS algorithm is proposed to deal with situation when the desired signal is strong for example, speech signal. Simulations were carried out using real speech signal with different noise power levels. Results demonstrate the superiority of the proposed NDLMS algorithm over LMS algorithm in achieving much smaller steady state excess mean square error.