Click to open the HelpDesk interface
AECE - Front page banner

Menu:


FACTS & FIGURES

JCR Impact Factor: 0.800
JCR 5-Year IF: 1.000
SCOPUS CiteScore: 2.0
Issues per year: 4
Current issue: Feb 2024
Next issue: May 2024
Avg review time: 78 days
Avg accept to publ: 48 days
APC: 300 EUR


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


TRAFFIC STATS

2,497,323 unique visits
994,103 downloads
Since November 1, 2009



Robots online now
Googlebot
bingbot


SCOPUS CiteScore

SCOPUS CiteScore


SJR SCImago RANK

SCImago Journal & Country Rank




TEXT LINKS

Anycast DNS Hosting
MOST RECENT ISSUES

 Volume 24 (2024)
 
     »   Issue 1 / 2024
 
 
 Volume 23 (2023)
 
     »   Issue 4 / 2023
 
     »   Issue 3 / 2023
 
     »   Issue 2 / 2023
 
     »   Issue 1 / 2023
 
 
 Volume 22 (2022)
 
     »   Issue 4 / 2022
 
     »   Issue 3 / 2022
 
     »   Issue 2 / 2022
 
     »   Issue 1 / 2022
 
 
 Volume 21 (2021)
 
     »   Issue 4 / 2021
 
     »   Issue 3 / 2021
 
     »   Issue 2 / 2021
 
     »   Issue 1 / 2021
 
 
  View all issues  


FEATURED ARTICLE

Analysis of the Hybrid PSO-InC MPPT for Different Partial Shading Conditions, LEOPOLDINO, A. L. M., FREITAS, C. M., MONTEIRO, L. F. C.
Issue 2/2022

AbstractPlus






LATEST NEWS

2023-Jun-28
Clarivate Analytics published the InCites Journal Citations Report for 2022. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.800 (0.700 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 1.000.

2023-Jun-05
SCOPUS published the CiteScore for 2022, computed by using an improved methodology, counting the citations received in 2019-2022 and dividing the sum by the number of papers published in the same time frame. The CiteScore of Advances in Electrical and Computer Engineering for 2022 is 2.0. For "General Computer Science" we rank #134/233 and for "Electrical and Electronic Engineering" we rank #478/738.

2022-Jun-28
Clarivate Analytics published the InCites Journal Citations Report for 2021. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.825 (0.722 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 0.752.

2022-Jun-16
SCOPUS published the CiteScore for 2021, computed by using an improved methodology, counting the citations received in 2018-2021 and dividing the sum by the number of papers published in the same time frame. The CiteScore of Advances in Electrical and Computer Engineering for 2021 is 2.5, the same as for 2020 but better than all our previous results.

2021-Jun-30
Clarivate Analytics published the InCites Journal Citations Report for 2020. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 1.221 (1.053 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 0.961.

Read More »


    
 

  1/2017 - 4

 HIGHLY CITED PAPER 

Comparison of Cepstral Normalization Techniques in Whispered Speech Recognition

GROZDIC, D. See more information about GROZDIC, D. on SCOPUS See more information about GROZDIC, D. on IEEExplore See more information about GROZDIC, D. on Web of Science, JOVICIC, S. See more information about  JOVICIC, S. on SCOPUS See more information about  JOVICIC, S. on SCOPUS See more information about JOVICIC, S. on Web of Science, SUMARAC PAVLOVIC, D. See more information about  SUMARAC PAVLOVIC, D. on SCOPUS See more information about  SUMARAC PAVLOVIC, D. on SCOPUS See more information about SUMARAC PAVLOVIC, D. on Web of Science, GALIC, J. See more information about  GALIC, J. on SCOPUS See more information about  GALIC, J. on SCOPUS See more information about GALIC, J. on Web of Science, MARKOVIC, B. See more information about MARKOVIC, B. on SCOPUS See more information about MARKOVIC, B. on SCOPUS See more information about MARKOVIC, B. on Web of Science
 
View the paper record and citations in View the paper record and citations in Google Scholar
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 (1,179 KB) | Citation | Downloads: 1,086 | Views: 3,289

Author keywords
automatic speech recognition, cepstral analysis, hidden Markov models, speech analysis, whisper

References keywords
speech(26), recognition(13), whispered(12), hansen(6), whisper(5), signal(5), processing(5), jovicic(5), grozdic(4), boril(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2017-02-28
Volume 17, Issue 1, Year 2017, On page(s): 21 - 26
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2017.01004
Web of Science Accession Number: 000396335900004
SCOPUS ID: 85014204959

Abstract
Quick view
Full text preview
This article presents an analysis of different cepstral normalization techniques in automatic recognition of whispered and bimodal speech (speech+whisper). In these experiments, conventional GMM-HMM speech recognizer was used as speaker-dependant automatic speech recognition system with special Whi-Spe corpus containing utterance recordings in normally phonated speech and whisper. The following normalization techniques were tested and compared: CMN (Cepstral Mean Normalization), CVN (Cepstral Variance Normalization), MVN (Cepstral Mean and Variance Normalization), CGN (Cepstral Gain Normalization) and quantile-based dynamic normalization techniques such as QCN and QCN-RASTA. The experimental results show to what extent each of these cepstral normalization techniques can improve whisper recognition accuracy in mismatched train/test scenario. The best result is obtained using CMN in combination with inverse filtering which provides an average 39.9 percent improvement in whisper recognition accuracy for all tested speakers.


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

[1] C. Zhang, J. H. L. Hansen, "Analysis and Classification of Speech Mode: Whisper through Shouted," in Proc. 8th Annu. Conf. Int. Speech Commun. Assoc. Interspeech 2007, Antwerp, 2007, pp. 2289-2292.

[2] T. Ito, K. Takeda, F. Itakura, "Analysis and recognition of whispered Speech," Speech Communication, vol. 45, pp. 139-152, Feb. 2005.
[CrossRef] [Web of Science Times Cited 116]


[3] D. T. Grozdic, J. Galic, B. Markovic, S. T. Jovicic, "Application of neural networks in whispered speech recognition," Telfor Journal, vol. 5, pp. 103-106, Nov. 2013.

[4] M. E. Ayadi, M. S. Kamel, F. Karray, "Survey on speech emotion recognition: Features, classification schemes and databases," Pattern Recognition, vol. 44, pp. 572-587, Mar. 2011.

[5] H. Boril, J. H. L. Hansen, "UT-Scope: Towards LVCSR under Lombard effect induced by varying types and levels of noisy background," in Proc. IEEE Int. Conf. Acoust. Speech Signal, ICASSP, Prague, 2011, pp. 4472-4475.
[CrossRef]


[6] S. Ghaffarzadegan, H. Boril, J. H. L. Hansen, "UT-Vocal Effort II: Analysis and constrained-lexicon recognition of whispered speech," in Proc. IEEE Int. Conf. Acoust. Speech Signal, ICASSP, Florence, Italy, 2014, pp. 2544-2548.
[CrossRef]


[7] A. Mathur, S. M. Reddy, R. M. Hegde, "Significance of parametric spectral ratio methods in detection and recognition of whispered speech." EURASIP J. Adv. Signal Process., pp. 157-177, Dec. 2012.

[8] C. Y. Yang, G. Brown, L. Lu, J. Yamagishi, S. King, "Noise-robust whispered speech recognition using a non-audible-murmur microphone with VTS compensation," in Proc. 8th International Symposium on Chinese Spoken Language Processing, ISCSLP, Hong Kong, China, 2012, pp. 220-223.
[CrossRef]


[9] R. W. Morris, "Enhancement and recognition of whispered speech," Ph.D. dissertation, School of Electrical and Computer Engineering, Georgia Institute of Technology, August 2003.

[10] D. T. Grozdic, S. T. Jovicic, M. Subotic, "Whispered speech recognition using deep denoising autoencoder," Engineering Applications of Artificial Intelligence, vol. 59, pp. 15-22, Mar. 2017.
[CrossRef] [Web of Science Times Cited 48]


[11] V. C. Tartter, "What's in a whisper?," Journal of the Acoustical Society of America, vol. 86, 1678-1683, 1989.

[12] B. P. Lim, "Computational differences between whispered and non-whispered speech." Ph.D. thesis, University of Illinois at Urbana-Champaign, 2011.

[13] D. T. Grozdic, S. T. Jovicic, J. Galic, B. Markovic, "Application of inverse filtering in enhancement of whisper recognition," in Proc. 12th Symp. Neural Netw. Appl. Electr. Eng., NEUREL 2014, Belgrade, 2014, pp. 157-161.
[CrossRef]


[14] B. Markovic, S. T. Jovicic, J. Galic, D. T. Grozdic, "Whispered Speech Database: Design, Processing and Application," in Proc. 16th International Conference, TSD 2013, Pilsen, 2013, pp. 591-598.
[CrossRef]


[15] P. X. Lee, D. Wee, H. Si, Y. Toh, B. P. Lim, N. Chen, B. Ma, V.J. College, "A whispered Mandarin corpus for speech technology applications," in Proc. Annu. Conf. Int. Speech Commun. Assoc., INTERSPEECH, Singapore, 2014, pp. 1598-1602.

[16] C. Zhang, J. H. L. Hansen, "Whisper-island detection based on unsupervised segmentation with entropy-based speech feature processing." IEEE Trans. Audio, Speech Lang. Process. 19, 883-894, Aug. 2010.
[CrossRef] [Web of Science Times Cited 37]


[17] S. T. Jovicic, "Formant feature differences between whispered and voiced sustained vowels," Acta Acust., vol. 84 (4), pp. 739-743, Jul. 1998.

[18] H. Boril, J. H. L. Hansen, "Unsupervised equalization of Lombard effect for speech recognition in noisy adverse environments," IEEE Transactions on Audio, Speech, and Language Processing, vol. 18 (6), pp. 1379-1393, Aug. 2010.
[CrossRef] [Web of Science Times Cited 55]


[19] B. Atal, "Effectiveness of linear prediction characteristics of the speech wave for automatic speaker identification and verification," J. Acoust. Soc. Am., vol. 55, pp. 1304-1312, 1974.
[CrossRef]


[20] S. J. Hahm, H. Boril, A. Pongtep, J.H.L. Hansen, "Advanced Feature Normalization and Rapid Model Adaptation for Robust In-Vehicle Speech Recognition," in Proc. 6th Biennial Workshop on Digital Signal Processing for In-Vehicle Systems, Seoul, 2013, pp. 14-17.

[21] S. Yoshizawa, N. Hayasaka, N. Wada, Y. Miyanaga, "Cepstral gain normalization for noise robust speech recognition," in Proc. IEEE Int. Conf. Acoust. Speech, Signal Process., Montreal, 2004, pp. 209-212.

[22] N. P. Solomon, G. N. McCall, M. W. Trosset, W. C. Gray, "Laryngeal configuration and constriction during two types of whispering," Journal of Speech and Hearing Research, vol. 32, pp. 161-174, Mar. 1989.

[23] P. Monoson, W. R. Zemlin, "Quantitative study of whisper," Folia Phoniatrica, vol. 36, pp. 53-65, 1984.



References Weight

Web of Science® Citations for all references: 256 TCR
SCOPUS® Citations for all references: 0

Web of Science® Average Citations per reference: 11 ACR
SCOPUS® Average Citations per reference: 0

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 2024-03-26 23:42 in 58 seconds.




Note1: Web of Science® is a registered trademark of Clarivate Analytics.
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 ©2001-2024
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: 


DNS Made Easy