1. Presentations on “ADAPTIVE LMS FILTERING APPROACH FOR SPEECH ENHANCEMENT” Approved By Presented By Mr. Rupesh Dubey Lalit P. Patil HOD (Elec & comm.) ( Elec & Comm. Engg)

2. OUTLINE AIM OF THE PROJECTS INTERDUCTION OF ADAPTIVE FILTER BLOCK REPRESENTATION OF ADAPTIVE FILTER INTERDUCTION OF LMS FILTER  METHODS –STEEPEST & DESCENT  ANALYSIS OF ADAPTIVE LMS FILTERING  ADAPTIVE NOISE CANCELLER MODEL 1) FOR SINGLE MICROPHONE 2) FOR TWO MICROPHONE USED TOOLS REFRENCES

3. In this project to removal of noise from speech signals. The algorithm yields better results in noise reduction with less distortions and artificial noise.

4. INTRODUCTION OF ADAPTIVE FILTER The sample-adaptive filter which has a number of advantages over the block-adaptive filters. It includes lower processing delay and better tracking of the trajectory of nonstationary signals.

5. These are essential characteristics in applications such as _ > echo cancellation > adaptive delay estimation > noise estimation > channel equalization in mobile telephony where low delay and fast tracking of time-varying processes and time- varying environments are important objectives.

7. LMS FILTER The LMS algorithm is a stochastic gradient algorithm in that it iterates each tap weight of the transversal filter in the direction of the instantaneous gradient of the squared error signal with respect to the tap weight in question. The LMS filter is very simple in computational terms. Its mathematical analysis is profoundly complicated because of its stochastic and nonlinear nature.

8. METHODOLOGY– STEEPEST & DESCENT The mean square error is reduced with each change in the weight vector. The process will converge on stationary point (minimum) regardless of the choice of initial weights. The surface of the mean square output error of an adaptive FIR filter, with respect to the filter coefficients, is a quadratic bowl-shaped curve, with a signal global minimum that corresponds to the LSE filter coefficients.

9. ADAPTIVE LMS FILTERING

12. Used tools MATLAB 7.8.0 is used for the simulation procedure in this project. MATLAB:-MATLAB which stands for Matrix Laboratory, is a software to facilitate numerical computations as well as some symbolic manipulation MATLAB is an interactive software system for numerical computations and graphics. USE OF MATLAB:-Using the MATLAB product, you can solve technical problems faster than with traditional programming languages, such as C, C++, and FORTRAN.

13. Used tools

15. REFRENCES Saeed V. Vaseghi, Multimedia Signal Processing, John Wiley & sons Ltd, 2007 Emanuel A.P. Habets, Sharon Gannot and Israel Cohen, “Dual-microphone speech Deverberation in a noisy environment”, IEEE International Symposium on signal processing and Information Technology, 2006. Paul W.Shields and Dougals R. Campbell, “Multi-microphone sub-band adaptive signal processing for improvement of hearing aid performance preliminary results using normal hearing voluntreers”, Proc. of the IEEE International Conference on Acoustics, speech, and Signal Processing, 1997 L.R.Rabiner/ R.W.Schafer, Digital processing of speech signals.

16. THANK YOU ANY ????????