Design and Implementation of Modified Adaptive Filtering Algorithm for Noise Cancellation in Speech Signal on FPGA for Minimum Resource Usage
Kartheek.B.V1, Manojkumar.S.B2, M.B.Anandaraju3

1Kartheek.B.V, PG Student, VLSI Design and Embedded System, B.G.S. Institute of technology, B.G.Nagar, Mandya-571448, Karnataka, India.
2Manojkumar.S.B, Assistant Professor, Department of Electronics and Communication Engineering, B.G.S. Institute of technology, B.G.Nagar, Mandya-571448, Karnataka, India.
3Prof. M.B.Anandaraju, Professor & HOD, Department of Electronics and Communication Engineering, B.G.S. Institute of technology, B.G.Nagar, Mandya-571448, Karnataka, India.
Manuscript received on June 02, 2013. | Revised Manuscript Received on June 10, 2013. | Manuscript published on June 20, 2013. | PP: 18-21 | Volume-1, Issue-7, June 2013. | Retrieval Number: G0232061713/2013©BEIESP
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© The Authors. Published By: Blue Eyes Intelligence Engineering & Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: In recent years FPGA systems are replacing dedicated Programmable Digital Signal Processor (PDSP) systems due to their greater flexibility and higher bandwidth, resulting from their parallel architecture. This paper presents the applicability of a FPGA system for speech processing. Here adaptive filtering technique is used for noise cancellation in speech signal. Least Mean Squares (LMS), one of the widely used algorithms in many signals processing environment, is implemented for adaption of the filter coefficients. The cancellation system is implemented in VHDL and tested for noise cancellation in speech signal. The simulation of VHDL design of adaptive filter is performed and analysed on the basis of Signal to Noise ratio (SNR) and Mean Square Error (MSE).When compared with previous methodology this paper achieves nearly 93% of accuracy.
Keywords: Adaptive Filter, LMS Algorithm, Active Noise cancellation, VHDL Design, SNR, MSE