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Implementation & Performance of Different Adaptive Filtering Algorithms for Speech Enhancement

Kapil Belpatre, M. R. Bachute, R. D. Kharadkar


Speech Enhancement deals with improvement of quality of speech signal corrupted by additive noise. For this purpose different methods are available out of which this paper deals with use of different algorithms in Adaptive Filter. It is a primary method to filter noise signal, because it does not need the signal statistical characteristics. In many applications for e.g. speech recognition, speaker identification and noise cancellation. Out of that noise cancellation is great challenge, as changes in speech characteristics could be quite fast. Thus adaptive algorithms require the utilization that converges rapidly is required. Now, in this case we deal with implementation of different Adaptive algorithms for improvement of degraded signal. Different parameters such as Mean Square Error, Computational time and the most important thing is Signal to Noise ratio is considered. It has been observed that the performance of different implemented as well as modified algorithms is better with respect to each of different parameters such as MSE, SNR & speed .In this paper we have compared different existing algorithms & newly implemented algorithms.


Least Mean Squares (LMS), Mean Square Error (MSE), Normalized Least Mean Squares (NLMS), Recursive Least Square (RLS), Signal to Noise ratio (SNR).

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