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Kharadkar, R. D.
- Performance Comparison of Affine Projection Algorithm and Normalized Kernel Affine Projection Algorithm for Speech Enhancement
Authors
1 Dept. of Electronics and Telecommunication, G. H. Raisoni Institute of Engineering and Technology, Pune, IN
Source
Digital Signal Processing, Vol 6, No 5 (2014), Pagination: 141-146Abstract
The main objective of the Speech Enhancement system is to improve the intelligibility and the quality of degraded speech signal. This paper emphasize on enhancement of noisy speech by using Affine Projection Algorithm (APA) and Kernel Affine Projection Algorithm (KAPA). Noise is present everywhere in the environment, So Kernel adaptive filters are used to enhance noisy speech signal and shows the good results in increasing the signal to Noise Ratio (SNR) and minimizing the mean square error (MSE). The computer simulations are performed using NOIZEUS speech corpus for different SNR values using Affine projection (APA), Kernel Affine projection (KAPA), Kernel normalized least mean square (KNLMS), Kernel affine projection with coherent criteria (KAPCC), and Extended kernel recursive least square (EXKRLS) their performance is compared.
Keywords
Speech Enhancement, APA, KAPA, RKHS, MSE, SNR.
- Implementation & Performance of Different Adaptive Filtering Algorithms for Speech Enhancement
Authors
1 Someshwarnagar, Pune,Maharashtra, IN
2 G. H. Raisoni Institute of Engineering and Technology, Pune, Maharashtra, IN
3 G. H. Raisoni Institute of Engineering and Technology, Pune, Maharashtra, IN
Source
Digital Signal Processing, Vol 6, No 5 (2014), Pagination: 147-155Abstract
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.