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FACTS & FIGURES

JCR Impact Factor: 1.102
JCR 5-Year IF: 0.734
Issues per year: 4
Current issue: Feb 2021
Next issue: May 2021
Avg review time: 54 days


PUBLISHER

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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LATEST NEWS

2020-Jun-29
Clarivate Analytics published the InCites Journal Citations Report for 2019. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 1.102 (1.023 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 0.734.

2020-Jun-11
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2019-Jun-20
Clarivate Analytics published the InCites Journal Citations Report for 2018. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.650, and the JCR 5-Year Impact Factor is 0.639.

2018-May-31
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  3/2012 - 12

Automatic Recognition of Improperly Pronounced Initial 'r' Consonant in Romanian

VELICAN, V. See more information about VELICAN, V. on SCOPUS See more information about VELICAN, V. on IEEExplore See more information about VELICAN, V. on Web of Science, STRUNGARU, R. See more information about  STRUNGARU, R. on SCOPUS See more information about  STRUNGARU, R. on SCOPUS See more information about STRUNGARU, R. on Web of Science, GRIGORE, O. See more information about GRIGORE, O. on SCOPUS See more information about GRIGORE, O. on SCOPUS See more information about GRIGORE, O. on Web of Science
 
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 (856 KB) | Citation | Downloads: 462 | Views: 2,795

Author keywords
speech processing, pronunciation evaluation

References keywords
speech(16), link(9), grigore(8), therapy(7), impaired(6), velican(5), system(5), schipor(5), recognition(5), language(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2012-08-31
Volume 12, Issue 3, Year 2012, On page(s): 79 - 84
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2012.03012
Web of Science Accession Number: 000308290500012
SCOPUS ID: 84865836127

Abstract
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Correctly assessing the degree of mispronunciation and deciding upon the necessary treatment are fundamental activities for all speech disorder specialists. Obviously, the experience and the availability of the specialists are essentials in order to assure an efficient therapy for the speech impaired. To overcome this deficiency a more objective approach would include the existence of a tool that independent of the specialist's abilities could be used to establish the diagnostics. A complete automated system based on speech processing algorithms capable of performing the recognition task is therefore thoroughly justified and can be viewed as a goal that will bring many benefits to the field of speech pronunciation correction. This paper presents further results of the authors' work on developing speech processing algorithms able to identify mispronunciations in Romanian language, more exactly we propose the use of the Walsh-Hadamard Transform (WHT) as feature selection tool in the case of identifying rhotacism. The results are encouraging with a best recognition rate of 92.55%.


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Cited-By SCOPUS

SCOPUS® Times Cited: 4
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Cited-By CrossRef

[1] Analysis of Hyperspectral Images Using Supervised Learning Techniques, Bilius, Laura-Bianca, Pentiuc, Stefan-Gheorghe, Brie, David, Miron, Sebastian, 2019 23rd International Conference on System Theory, Control and Computing (ICSTCC), ISBN 978-1-7281-0699-1, 2019.
Digital Object Identifier: 10.1109/ICSTCC.2019.8885627
[CrossRef]

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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania


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