Click to open the HelpDesk interface
AECE - Front page banner

Menu:


FACTS & FIGURES

JCR Impact Factor: 0.459
JCR 5-Year IF: 0.442
Issues per year: 4
Current issue: Nov 2016
Next issue: Feb 2017
Avg review time: 97 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: 644266260
doi: 10.4316/AECE


TRAFFIC STATS

1,464,144 unique visits
469,871 downloads
Since November 1, 2009



No robots online now


SJR SCImago RANK

SCImago Journal & Country Rank


SEARCH ENGINES

aece.ro - Google Pagerank




TEXT LINKS

Anycast DNS Hosting
MOST RECENT ISSUES

 Volume 16 (2016)
 
     »   Issue 4 / 2016
 
     »   Issue 3 / 2016
 
     »   Issue 2 / 2016
 
     »   Issue 1 / 2016
 
 
 Volume 15 (2015)
 
     »   Issue 4 / 2015
 
     »   Issue 3 / 2015
 
     »   Issue 2 / 2015
 
     »   Issue 1 / 2015
 
 
 Volume 14 (2014)
 
     »   Issue 4 / 2014
 
     »   Issue 3 / 2014
 
     »   Issue 2 / 2014
 
     »   Issue 1 / 2014
 
 
 Volume 13 (2013)
 
     »   Issue 4 / 2013
 
     »   Issue 3 / 2013
 
     »   Issue 2 / 2013
 
     »   Issue 1 / 2013
 
 
  View all issues  








LATEST NEWS

2016-Jun-14
Thomson Reuters published the Journal Citations Report for 2015. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.459, and the JCR 5-Year Impact Factor is 0.442.

2015-Dec-04
Starting with Issue 2/2016, the article processing charge is 300 EUR for each article accepted for publication. The charge of 25 EUR per page for papers over 8 pages will not be changed. Details are available in the For authors section.

2015-Jun-10
Thomson Reuters published the Journal Citations Report for 2014. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.529, and the JCR 5-Year Impact Factor is 0.476.

2015-Feb-09
Starting on the 9th of February 2015, we require all authors to identify themselves, when a submission is made, by entering their SCOPUS Author IDs, instead of the organizations, when available. This information will let us better know the publishing history of the authors and better assign the reviewers on different topics.

2015-Feb-08
We have more than 500 author names on the ban-list for cheating, including plagiarism, false signatures on the copyright form, false E-mail addresses and even tentative to impersonate well-known researchers in order to become a reviewer of our Journal. We maintain a full history of such incidents.

Read More »


    
 

  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
 
Click to see author's profile on 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 (729 KB) | Citation | Downloads: 387 | Views: 1,832

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
Quick view
Full text preview
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

[1] F. Dellaert, T. Polzin, A. Waibel, "Recognizing emotion in speech," in International Conference on Spoken Language, Philadelphia, PA, USA, 1996, pp.1970-1973.
[CrossRef]


[2] D. Ververidis, C. Kotropoulos, "Emotional speech recognition: Resources, features, and methods," Speech Communication, vol. ED-48, pp. 1162-1181, 2006.
[CrossRef] [Web of Science Times Cited 252] [SCOPUS Times Cited 402]


[3] B. Schuller, G. Rigoll, "Timing levels in segment-based speech emotion recognition," in INTERSPEECH'2006, Pittsburgh, PA, USA, 2006, pp. 1818-1821.

[4] P. Oudeyer, "The production and recognition of emotions in speech: features and algorithms," International Journal of Human-Computer Studies, vol. ED-59, pp. 157-183, 2003.
[CrossRef] [Web of Science Times Cited 31] [SCOPUS Times Cited 224]


[5] R. Tato, R. Santos, R. Kompe, J. Pardo, "Emotional space improves emotion recognition," in International Conference on Spoken Language, Denver, CO, USA, 2002, pp. 2029-2032.

[6] B. Schuller, R. Müller, M. K. Lang, G. Rigoll, "Speaker independent emotion recognition by early fusion of acoustic and linguistic features within ensembles," in INTERSPEECH’2005, Lisbon, Portugal, 2005, pp. 805-808.

[7] B. Schuller, S. Reiter, R. Muller, M. Al-Hames, "Speaker independent speech emotion recognition by ensemble classification," in IEEE International Conf. Multimedia and Expo(ICME), Amsterdam, The Netherlands, 2005, pp. 864-867.
[CrossRef] [SCOPUS Times Cited 37]


[8] T. Kostoulas, T. Ganchev, N. Fakotakis, "Study on speaker-independent emotion recognition from speech on real-world data," in Verbal and nonverbal features of human-human and human-machine interaction, Springer Berlin Heidelberg, 2008, pp. 235-242.
[CrossRef] [SCOPUS Times Cited 2]


[9] M. Belkin, P. Niyogi, "Laplacian eigenmaps and spectral techniques for embedding and clustering," in Advances in Neutral Information Processing Systems(NIPS) 14, Vancouver, Canada, 2002, pp. 585-591.

[10] X. He, P. Niyogi, "Locality preserving projections," in Advances in Neural Information Processing Systems (NIPS) 16, Whistler, Canada, 2003, pp. 153-160.

[11] S. Roweis, L. Saul, "Nonlinear dimensionality reduction by locally linear embedding," Science, vol. ED-290(5500), pp. 2323-2326, 2000.
[CrossRef] [Web of Science Times Cited 4641] [SCOPUS Times Cited 6781]


[12] S. Lafon, A. Lee, "Diffusion maps and coarse-graining: A unified framework for dimensionality reduction, graph partitioning, and data set parameterization," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. ED-28(9), pp. 1393-1403, 2006.
[CrossRef] [Web of Science Times Cited 234] [SCOPUS Times Cited 287]


[13] J. Tenenbaum, V. de Silva, J. Langford, "A global geometric framework for nonlinear dimensionality reduction," Science, vol. ED-290, pp. 2319-2323, 2000.
[CrossRef] [Web of Science Times Cited 4274] [SCOPUS Times Cited 6308]


[14] H. Chen, H. Chang, T. Liu, "Local discriminant embedding and its variants," in IEEE Conf. Computer Vision and Pattern Recognition (CVPR), San Diego, CA, USA, 2005, pp. 846-853.
[CrossRef] [SCOPUS Times Cited 273]


[15] S. Yan, D. Xu, B. Zhang, H. Zhang, Q. Yang, S. Lin, "Graph embedding and extensions: a general framework for dimensionality reduction," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. ED-29(1), pp. 40-51, 2007.
[CrossRef] [Web of Science Times Cited 1072] [SCOPUS Times Cited 1410]


[16] F. De la Torre, "A least-squares framework for component analysis," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. ED-34(6), pp. 1041-1055, 2012.
[CrossRef] [Web of Science Times Cited 25] [SCOPUS Times Cited 49]


[17] M. You, C. Chen, J. Bu, J. Liu, J. Tao, "Emotional speech analysis on nonlinear manifold," in International Conference on Pattern Recognition(ICPR), Hong Kong, 2006, pp. 91-94.
[CrossRef] [SCOPUS Times Cited 4]


[18] S. Zhang, X. Zhao, B. Lei, "Speech emotion recognition using an enhanced Kernel Isomap for human-robot interaction," International Journal of Advanced Robotic Systems, vol. ED-10(114), pp. 1-7, 2013.
[CrossRef] [Web of Science Times Cited 1] [SCOPUS Times Cited 4]


[19] J. Shawe-Taylor, N. Cristianini, Kernel methods for pattern analysis. Cambridge University Press, 2004.

[20] Friedman J H, "Regularized discriminant analysis," Journal of the American Statistical Association, vol. ED-84(405), pp. 165-175, 1989.
[CrossRef] [SCOPUS Times Cited 1246]


[21] D. Cai, X. He, "Semi-supervised discriminant analysis," in International Conference on Computer Vision(ICCV). Rio de Janeiro, Brazil, 2007, pp. 1-7.
[CrossRef] [SCOPUS Times Cited 136]


[22] L. He, J. M. Buenaposada, L. Baumela, "An empirical comparison of graph-based dimensionality reduction algorithms on facial expression recognition tasks," in International Conf. Pattern Recognition (ICPR), Tampa, FL, USA, 2008, pp. 1-4.
[CrossRef]


[23] F. Burkhardt, A. Paeschke, M. Rolfes, W. F. Sendlmeier, B. Weiss, "A database of German emotional speech," in INTERSPEECH’2005, Lisbon, Portugal, 2005, pp. 1517-1520.

[24] O. Martin, I. Kotsia, B. Macq, I. Pitas, "The enterface'05 audio-visual emotion database," in IEEE Conf. Data Engineering Workshops, Atlanta, GA, USA, 2006, pp. 8-8.
[CrossRef] [SCOPUS Times Cited 6]




References Weight

Web of Science® Citations for all references: 10,530 TCR
SCOPUS® Citations for all references: 17,169 TCR

Web of Science® Average Citations per reference: 421 ACR
SCOPUS® Average Citations per reference: 687 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 2016-12-07 18:07 in 92 seconds.




Note1: Web of Science® is a registered trademark of Thomson Reuters.
Note2: SCOPUS® is a registered trademark of Elsevier B.V.
Disclaimer: All queries to the respective databases were made by using the DOI record of every reference (where available). Due to technical problems beyond our control, the information is not always accurate. Please use the CrossRef link to visit the respective publisher site.

Copyright ©2001-2016
Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania


All rights reserved: Advances in Electrical and Computer Engineering is a registered trademark of the Stefan cel Mare University of Suceava. No part of this publication may be reproduced, stored in a retrieval system, photocopied, recorded or archived, without the written permission from the Editor. When authors submit their papers for publication, they agree that the copyright for their article be transferred to the Faculty of Electrical Engineering and Computer Science, Stefan cel Mare University of Suceava, Romania, if and only if the articles are accepted for publication. The copyright covers the exclusive rights to reproduce and distribute the article, including reprints and translations.

Permission for other use: The copyright owner's consent does not extend to copying for general distribution, for promotion, for creating new works, or for resale. Specific written permission must be obtained from the Editor for such copying. Direct linking to files hosted on this website is strictly prohibited.

Disclaimer: Whilst every effort is made by the publishers and editorial board to see that no inaccurate or misleading data, opinions or statements appear in this journal, they wish to make it clear that all information and opinions formulated in the articles, as well as linguistic accuracy, are the sole responsibility of the author.




Website loading speed and performance optimization powered by: