Speckle Noise Detection and Removal for Laser Speech Measurement Systems

Laser speech measurement is a new sound capture technology based on Laser Doppler Vibrometry (LDV). It avoids the need for contact, is easily concealed and is ideal for remote speech acquisition, which has led to its wide-scale adoption for military and security applications. However, lasers are eas...

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Autores principales:	Yahui Wang, Wenxi Zhang, Zhou Wu, Xinxin Kong, Hongxin Zhang
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	laser speech measurement speech enhancement automatic speckle noise detection average short-time energy kurtosis Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
Acceso en línea:	https://doaj.org/article/a1b0c46ed47149b289a0a65c86007d2b
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spelling	oai:doaj.org-article:a1b0c46ed47149b289a0a65c86007d2b2021-11-11T14:59:35ZSpeckle Noise Detection and Removal for Laser Speech Measurement Systems10.3390/app112198702076-3417https://doaj.org/article/a1b0c46ed47149b289a0a65c86007d2b2021-10-01T00:00:00Zhttps://www.mdpi.com/2076-3417/11/21/9870https://doaj.org/toc/2076-3417Laser speech measurement is a new sound capture technology based on Laser Doppler Vibrometry (LDV). It avoids the need for contact, is easily concealed and is ideal for remote speech acquisition, which has led to its wide-scale adoption for military and security applications. However, lasers are easily affected by complex detection environments. Thus, speckle noise often appears in the measured speech, seriously affecting its quality and intelligibility. This paper examines all of the characteristics of impulsive noise in laser measured speech and proposes a novel automatic impulsive noise detection and removal method. This method first foregrounds noise using decorrelation based on a linear prediction (LP) model that improves the noise-to-signal ratio (NSR) of the measured signal. This makes it possible to detect the position of noise through a combination of the average short-time energy and kurtosis. The method not only precisely locates small clicks (with a duration of just a few samples), but also finds the location of longer bursts and scratches (with a duration of up to a hundred samples). The located samples can then be replaced by more appropriate samples whose coding is based on the LP model. This strategy avoids unnecessary processing and obviates the need to compromise the quality of the relatively large fraction of samples that are unaffected by speckle noise. Experimental results show that the proposed automatic speckle noise detection and removal method outperforms other related methods across a wide range of degraded audio signals.Yahui WangWenxi ZhangZhou WuXinxin KongHongxin ZhangMDPI AGarticlelaser speech measurementspeech enhancementautomatic speckle noise detectionaverage short-time energykurtosisTechnologyTEngineering (General). Civil engineering (General)TA1-2040Biology (General)QH301-705.5PhysicsQC1-999ChemistryQD1-999ENApplied Sciences, Vol 11, Iss 9870, p 9870 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	laser speech measurement speech enhancement automatic speckle noise detection average short-time energy kurtosis Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
spellingShingle	laser speech measurement speech enhancement automatic speckle noise detection average short-time energy kurtosis Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999 Yahui Wang Wenxi Zhang Zhou Wu Xinxin Kong Hongxin Zhang Speckle Noise Detection and Removal for Laser Speech Measurement Systems
description	Laser speech measurement is a new sound capture technology based on Laser Doppler Vibrometry (LDV). It avoids the need for contact, is easily concealed and is ideal for remote speech acquisition, which has led to its wide-scale adoption for military and security applications. However, lasers are easily affected by complex detection environments. Thus, speckle noise often appears in the measured speech, seriously affecting its quality and intelligibility. This paper examines all of the characteristics of impulsive noise in laser measured speech and proposes a novel automatic impulsive noise detection and removal method. This method first foregrounds noise using decorrelation based on a linear prediction (LP) model that improves the noise-to-signal ratio (NSR) of the measured signal. This makes it possible to detect the position of noise through a combination of the average short-time energy and kurtosis. The method not only precisely locates small clicks (with a duration of just a few samples), but also finds the location of longer bursts and scratches (with a duration of up to a hundred samples). The located samples can then be replaced by more appropriate samples whose coding is based on the LP model. This strategy avoids unnecessary processing and obviates the need to compromise the quality of the relatively large fraction of samples that are unaffected by speckle noise. Experimental results show that the proposed automatic speckle noise detection and removal method outperforms other related methods across a wide range of degraded audio signals.
format	article
author	Yahui Wang Wenxi Zhang Zhou Wu Xinxin Kong Hongxin Zhang
author_facet	Yahui Wang Wenxi Zhang Zhou Wu Xinxin Kong Hongxin Zhang
author_sort	Yahui Wang
title	Speckle Noise Detection and Removal for Laser Speech Measurement Systems
title_short	Speckle Noise Detection and Removal for Laser Speech Measurement Systems
title_full	Speckle Noise Detection and Removal for Laser Speech Measurement Systems
title_fullStr	Speckle Noise Detection and Removal for Laser Speech Measurement Systems
title_full_unstemmed	Speckle Noise Detection and Removal for Laser Speech Measurement Systems
title_sort	speckle noise detection and removal for laser speech measurement systems
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/a1b0c46ed47149b289a0a65c86007d2b
work_keys_str_mv	AT yahuiwang specklenoisedetectionandremovalforlaserspeechmeasurementsystems AT wenxizhang specklenoisedetectionandremovalforlaserspeechmeasurementsystems AT zhouwu specklenoisedetectionandremovalforlaserspeechmeasurementsystems AT xinxinkong specklenoisedetectionandremovalforlaserspeechmeasurementsystems AT hongxinzhang specklenoisedetectionandremovalforlaserspeechmeasurementsystems
_version_	1718437915572305920

Speckle Noise Detection and Removal for Laser Speech Measurement Systems

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