<?xml version="1.0" encoding="UTF-8"?> <article key="pdf/5946" mdate="2008-10-21 00:00:00"> <author>C. Ganesh Babu and P. T. Vanathi</author> <title>A Modified Speech Enhancement Using Adaptive Gain Equalizer with Non linear Spectral Subtraction for Robust Speech Recognition</title> <pages>2179 - 2183</pages> <year>2008</year> <volume>2</volume> <number>10</number> <journal>International Journal of Electrical and Computer Engineering</journal> <ee>https://publications.waset.org/pdf/5946</ee> <url>https://publications.waset.org/vol/22</url> <publisher>World Academy of Science, Engineering and Technology</publisher> <abstract>In this paper we present an enhanced noise reduction method for robust speech recognition using Adaptive Gain Equalizer with Non linear Spectral Subtraction. In Adaptive Gain Equalizer method (AGE), the input signal is divided into a number of subbands that are individually weighed in time domain, in accordance to the short time SignaltoNoise Ratio (SNR) in each subband estimation at every time instant. Instead of focusing on suppression the noise on speech enhancement is focused. When analysis was done under various noise conditions for speech recognition, it was found that Adaptive Gain Equalizer method algorithm has an obvious failing point for a SNR of 5 dB, with inadequate levels of noise suppression for SNR less than this point. This work proposes the implementation of AGE when coupled with Non linear Spectral Subtraction (AGENSS) for robust speech recognition. The experimental result shows that out AGENSS performs the AGE when SNR drops below 5db level. </abstract> <index>Open Science Index 22, 2008</index> </article>