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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229
ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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  4/2011 - 1
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 HIGHLY CITED PAPER 

Line Spectral Frequency-based Noise Suppression for Speech-Centric Interface of Smart Devices

JANG, G. J. See more information about JANG, G. J. on SCOPUS See more information about JANG, G. J. on IEEExplore See more information about JANG, G. J. on Web of Science, PARK, J. S. See more information about  PARK, J. S. on SCOPUS See more information about  PARK, J. S. on SCOPUS See more information about PARK, J. S. on Web of Science, KIM, J. H. See more information about  KIM, J. H. on SCOPUS See more information about  KIM, J. H. on SCOPUS See more information about KIM, J. H. on Web of Science, SEO, Y. H. See more information about SEO, Y. H. on SCOPUS See more information about SEO, Y. H. on SCOPUS See more information about SEO, Y. H. on Web of Science
 
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Click to see author's profile in See more information about the author on SCOPUS SCOPUS, See more information about the author on IEEE Xplore IEEE Xplore, See more information about the author on Web of Science Web of Science

Download PDF pdficon (708 KB) | Citation | Downloads: 2,125 | Views: 22

Author keywords
noise measurement, noise reduction, speech enhancement, speech recognition, linear predictive coding

References keywords
speech(15), spectral(6), processing(5), signal(4), recognition(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2011-11-30
Volume 11, Issue 4, Year 2011, On page(s): 3 - 8
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2011.04001
Web of Science Accession Number: 000297764500001
SCOPUS ID: 84863083144

Abstract
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This paper proposes a noise suppression technique for speech-centric interface of various smart devices. The proposed method estimates noise spectral magnitudes from line spectral frequencies (LSFs), using the observation that adjacent LSFs correspond to peak frequencies of spectrum, whereas isolated LSFs are close to flattened valley frequencies retaining noise components. Over a course of segmented time frames, the logarithms of spectral magnitudes at respective LSFs are computed, and their distribution is then modeled by the Rayleigh probability density function. The standard deviation from the Rayleigh function approximates the noise spectral magnitude. The model is updated at every frame in an online manner so that it can deal with real-time inputs. Once the noise spectral magnitude is estimated, a time-domain Wiener filter is derived for the suppression of the estimated noise spectral magnitude, and this is then applied to the input noisy speech signals. Our proposed approach operates well on most smart devices owing to its low computational complexity and real-time implementation. Speech recognition experiments, conducted to evaluate the proposed technique, show that our method exhibits superior performance, with less distortion of original speech, when compared to conventional noise suppression techniques.


References | Cited By

Cited-By Clarivate Web of Science

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Cited-By SCOPUS

SCOPUS® Times Cited: 5
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Cited-By CrossRef

[1] Particle filtering based pitch sequence correction for monaural speech segregation, Kim, Han‐Gyu, Jang, Gil‐Jin, Park, Jeong‐Sik, Kim, Ji‐Hwan, Oh, Yung‐Hwan, International Journal of Imaging Systems and Technology, ISSN 0899-9457, Issue 1, Volume 23, 2013.
Digital Object Identifier: 10.1002/ima.22039
[CrossRef]

[2] Acoustic interference cancellation for a voice-driven interface in smart TVs, Park, Jeong-Sik, Jang, Gil-Jin, Kim, Ji-Hwan, Kim, Sang-Hoon, IEEE Transactions on Consumer Electronics, ISSN 0098-3063, Issue 1, Volume 59, 2013.
Digital Object Identifier: 10.1109/TCE.2013.6490266
[CrossRef]

[3] Unsupervised noise reduction scheme for voice-based information retrieval in mobile environments, Park, Jeong-Sik, Jang, Gil-Jin, Kim, Ji-Hwan, Yeo, Sang-Soo, Multimedia Tools and Applications, ISSN 1380-7501, Issue 9, Volume 75, 2016.
Digital Object Identifier: 10.1007/s11042-013-1788-y
[CrossRef]

[4] Particle filtering by sigmoidal weight update for speech pitch correction, Kim, Han-Gyu, Park, Jeong-Sik, Jang, Gil-Jin, Oh, Yung-Hwan, 2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC), ISBN 978-1-4673-1714-6, 2012.
Digital Object Identifier: 10.1109/ICSMC.2012.6378133
[CrossRef]

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