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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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2017-Jun-14
Thomson Reuters published the Journal Citations Report for 2016. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.595, and the JCR 5-Year Impact Factor is 0.661.

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2017-Feb-16
With new technologies, such as mobile communications, internet of things, and wide applications of social media, organizations generate a huge volume of data, much faster than several years ago. Big data, characterized by high volume, diversity and velocity, increasingly drives decision making and is changing the landscape of business intelligence, from governments to private organizations, from communities to individuals. Big data analytics that discover insights from evidences has a high demand for computing efficiency, knowledge discovery, problem solving, and event prediction. We dedicate a special section of Issue 4/2017 to Big Data. Prospective authors are asked to make the submissions for this section no later than the 31st of May 2017, placing "BigData - " before the paper title in OpenConf.

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  2/2014 - 3

Graph Learning Based Speaker Independent Speech Emotion Recognition

XU, X. See more information about XU, X. on SCOPUS See more information about XU, X. on IEEExplore See more information about XU, X. on Web of Science, HUANG, C. See more information about  HUANG, C. on SCOPUS See more information about  HUANG, C. on SCOPUS See more information about HUANG, C. on Web of Science, WU, C. See more information about  WU, C. on SCOPUS See more information about  WU, C. on SCOPUS See more information about WU, C. on Web of Science, WANG, Q. See more information about  WANG, Q. on SCOPUS See more information about  WANG, Q. on SCOPUS See more information about WANG, Q. on Web of Science, ZHAO, L. See more information about ZHAO, L. on SCOPUS See more information about ZHAO, L. on SCOPUS See more information about ZHAO, L. on Web of Science
 
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Download PDF pdficon (729 KB) | Citation | Downloads: 445 | Views: 2,279

Author keywords
speech emotion recognition, speaker penalty graph learning, graph embedding framework, dimensionality reduction

References keywords
recognition(12), speech(10), emotion(8), analysis(8), pattern(7), reduction(5), human(5), dimensionality(5), science(4), machine(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2014-05-31
Volume 14, Issue 2, Year 2014, On page(s): 17 - 22
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2014.02003
Web of Science Accession Number: 000340868100003
SCOPUS ID: 84901856862

Abstract
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In this paper, the algorithm based on graph learning and graph embedding framework, Speaker-Penalty Graph Learning (SPGL), is proposed in the research of speech emotion recognition to solve the problems caused by different speakers. Graph embedding framework theory is used to construct the dimensionality reduction stage of speech emotion recognition. Special penalty and intrinsic graphs of the graph embedding framework is proposed to penalize the impacts from different speakers in the task of speech emotion recognition. The original speech emotion features are extracted by various categories, reflecting different characteristics of each speech sample. According to the experiments in speech emotion corpus using different classifiers, the proposed method with linear and kernelized mapping forms can both achieve relatively better performance than the state-of-the-art dimensionality reduction methods.


References | Cited By  «-- Click to see who has cited this paper

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[CrossRef] [SCOPUS Times Cited 11]


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[CrossRef] [SCOPUS Times Cited 151]




References Weight

Web of Science® Citations for all references: 12,100 TCR
SCOPUS® Citations for all references: 19,776 TCR

Web of Science® Average Citations per reference: 484 ACR
SCOPUS® Average Citations per reference: 791 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2017-12-12 02:46 in 103 seconds.




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


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