Seed funding for strategic research @ RTP (research manpower­)

Modern voice authentication systems perform extremely well on large population high quality clean speech databases. While novel algorithms can be designed to provide performance and accuracy, the performance degrades rapidly in the presence of noise. Noise introduces a mismatch between the verificat...

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Main Author: Thambipillai Srikanthan.
Other Authors: School of Computer Engineering
Format: Research Report
Language:English
Published: 2009
Subjects:
Online Access:http://hdl.handle.net/10356/17242
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Institution: Nanyang Technological University
Language: English
id sg-ntu-dr.10356-17242
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spelling sg-ntu-dr.10356-172422023-03-03T20:22:01Z Seed funding for strategic research @ RTP (research manpower­) Thambipillai Srikanthan. School of Computer Engineering DRNTU::Engineering::Computer science and engineering::Computing methodologies::Pattern recognition Modern voice authentication systems perform extremely well on large population high quality clean speech databases. While novel algorithms can be designed to provide performance and accuracy, the performance degrades rapidly in the presence of noise. Noise introduces a mismatch between the verification utterance and the speaker template which causes unpredictable scores leading to performance degradation. Our research attempts to address the problem of mismatch condition caused by additive noise. We have proposed novel algorithms for noise compensation in the speaker model domain and demonstrated their efficiency on TIMIT database corrupted with additive noise. Subsequently, we have combined the proposed algorithm with spectral subtraction method to further improve the performance of the authentication have been successfully translated to dedicated hardware architecture and prototyped on FPGA-based platforms. RGM 11/04 2009-06-02T01:54:16Z 2009-06-02T01:54:16Z 2008 2008 Research Report http://hdl.handle.net/10356/17242 en 39 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Computer science and engineering::Computing methodologies::Pattern recognition
spellingShingle DRNTU::Engineering::Computer science and engineering::Computing methodologies::Pattern recognition
Thambipillai Srikanthan.
Seed funding for strategic research @ RTP (research manpower­)
description Modern voice authentication systems perform extremely well on large population high quality clean speech databases. While novel algorithms can be designed to provide performance and accuracy, the performance degrades rapidly in the presence of noise. Noise introduces a mismatch between the verification utterance and the speaker template which causes unpredictable scores leading to performance degradation. Our research attempts to address the problem of mismatch condition caused by additive noise. We have proposed novel algorithms for noise compensation in the speaker model domain and demonstrated their efficiency on TIMIT database corrupted with additive noise. Subsequently, we have combined the proposed algorithm with spectral subtraction method to further improve the performance of the authentication have been successfully translated to dedicated hardware architecture and prototyped on FPGA-based platforms.
author2 School of Computer Engineering
author_facet School of Computer Engineering
Thambipillai Srikanthan.
format Research Report
author Thambipillai Srikanthan.
author_sort Thambipillai Srikanthan.
title Seed funding for strategic research @ RTP (research manpower­)
title_short Seed funding for strategic research @ RTP (research manpower­)
title_full Seed funding for strategic research @ RTP (research manpower­)
title_fullStr Seed funding for strategic research @ RTP (research manpower­)
title_full_unstemmed Seed funding for strategic research @ RTP (research manpower­)
title_sort seed funding for strategic research @ rtp (research manpower­)
publishDate 2009
url http://hdl.handle.net/10356/17242
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