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International Journal of Scientific Development and Research - IJSDR
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Paper Title: SPEECH DE-NOISING USING FUNCTIONAL LINK ARTIFICIAL NEURAL NETWORK
Authors Name: Niraj Kumar Shukla , Silpa Nayak , Ravi Kant Jha
Unique Id: IJSDR1604032
Published In: Volume 1 Issue 4, April-2016
Abstract: Speech processing is a major field of use in present day. When an Speech sent from source to destination, it gets noisy due to different reasons. Mainly this noise added at the time of acquisition, processing and at the time of transmission of the speech signal. Low light level, sensor temperatures, sensor noise, poor illumination, high temperature of the surroundings are the major factor affecting the speech Again when this speech transmitted to the destination, it corrupted due to interference in the channel use for transmission. Speech signal Image transmitted from in wireless network might be corrupted as a result of lighting or other atmospheric disturbances. Different noises added in this image are additive white Gaussian noise, salt and pepper noise, Both Gaussian and salt and pepper noise, Rayleigh Noise, Erlang Noise, Exponential Noise, Uniform Noise, and Periodic Noise etc. In this paper various noise conditions are studied and efficient adaptive filters based on Functional link artificial neural network are designed to suppress Gaussian noise. The developed filters may use for offline or for online applications interference in the channel use for transmission. In this paper various noise conditions are studied and efficient adaptive filters based on Functional link artificial neural network are designed to suppress Gaussian noise.
Keywords: NEURAL NETWORK, FLANN, SS, ASR etc.
Cite Article: "SPEECH DE-NOISING USING FUNCTIONAL LINK ARTIFICIAL NEURAL NETWORK", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.1, Issue 4, page no.202 - 206, April-2016, Available :http://www.ijsdr.org/papers/IJSDR1604032.pdf
Downloads: 0001958
Publication Details: Published Paper ID: IJSDR1604032
Registration ID:160162
Published In: Volume 1 Issue 4, April-2016
DOI (Digital Object Identifier):
Page No: 202 - 206
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631

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