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

2,501,171 unique visits
994,937 downloads
Since November 1, 2009



Robots online now
Googlebot


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

Application of the Voltage Control Technique and MPPT of Stand-alone PV System with Storage, HIVZIEFENDIC, J., VUIC, L., LALE, S., SARIC, M.
Issue 1/2022

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 »


    
 

  1/2015 - 9

 HIGHLY CITED PAPER 

Enhancing ASR Systems for Under-Resourced Languages through a Novel Unsupervised Acoustic Model Training Technique

CUCU, H. See more information about CUCU, H. on SCOPUS See more information about CUCU, H. on IEEExplore See more information about CUCU, H. on Web of Science, BUZO, A. See more information about  BUZO, A. on SCOPUS See more information about  BUZO, A. on SCOPUS See more information about BUZO, A. on Web of Science, BESACIER, L. See more information about  BESACIER, L. on SCOPUS See more information about  BESACIER, L. on SCOPUS See more information about BESACIER, L. on Web of Science, BURILEANU, C. See more information about BURILEANU, C. on SCOPUS See more information about BURILEANU, C. on SCOPUS See more information about BURILEANU, C. 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 (612 KB) | Citation | Downloads: 811 | Views: 3,918

Author keywords
speech recognition, under-resourced languages, unsupervised acoustic modeling, unsupervised training

References keywords
speech(15), training(13), unsupervised(12), resourced(5), recognition(5), processing(5), languages(5), language(5), acoustic(5), system(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2015-02-28
Volume 15, Issue 1, Year 2015, On page(s): 63 - 68
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2015.01009
Web of Science Accession Number: 000352158600009
SCOPUS ID: 84924787729

Abstract
Quick view
Full text preview
Statistical speech and language processing techniques, requiring large amounts of training data, are currently state-of-the-art in automatic speech recognition. For high-resourced, international languages this data is widely available, while for under-resourced languages the lack of data poses serious problems. Unsupervised acoustic modeling can offer a cost and time effective way of creating a solid acoustic model for any under-resourced language. This study describes a novel unsupervised acoustic model training method and evaluates it on speech data in an under-resourced language: Romanian. The key novel factor of the method is the usage of two complementary seed ASR systems to produce high quality transcriptions, with a Character Error Rate (ChER) < 5%, for initially untranscribed speech data. The methodology leads to a relative Word Error Rate (WER) improvement of more than 10% when 100 hours of untranscribed speech are used.


References | Cited By

Cited-By Clarivate Web of Science

Web of Science® Times Cited: 4 [View]
View record in Web of Science® [View]
View Related Records® [View]

Updated today


Cited-By SCOPUS

SCOPUS® Times Cited: 5
View record in SCOPUS®
[Free preview]
View citations in SCOPUS® [Free preview]

Updated today

Cited-By CrossRef

[1] Semi-Supervised Training of Language Model on Spanish Conversational Telephone Speech Data, Egorova, Ekaterina, Serrano, Jordi Luque, Procedia Computer Science, ISSN 1877-0509, Issue , 2016.
Digital Object Identifier: 10.1016/j.procs.2016.04.038
[CrossRef]

[2] Progress on automatic annotation of speech corpora using complementary ASR systems, Georgescu, Alexandru-Lucian, Cucu, Horia, Burileanu, Corneliu, 2019 42nd International Conference on Telecommunications and Signal Processing (TSP), ISBN 978-1-7281-1864-2, 2019.
Digital Object Identifier: 10.1109/TSP.2019.8769087
[CrossRef]

[3] Automatic Annotation of Speech Corpora using Approximate Transcripts, Manolache, Cristian, Georgescu, Alexandru-Lucian, Caranica, Alexandru, Cucu, Horia, 2020 43rd International Conference on Telecommunications and Signal Processing (TSP), ISBN 978-1-7281-6376-5, 2020.
Digital Object Identifier: 10.1109/TSP49548.2020.9163405
[CrossRef]

[4] Automatic Annotation of Speech Corpora Using Complementary GMM and DNN Acoustic Models, Georgescu, Alexandru-Lucian, Cucu, Horia, 2018 41st International Conference on Telecommunications and Signal Processing (TSP), ISBN 978-1-5386-4695-3, 2018.
Digital Object Identifier: 10.1109/TSP.2018.8441374
[CrossRef]

[5] Data-Filtering Methods for Self-Training of Automatic Speech Recognition Systems, Georgescu, Alexandru-Lucian, Manolache, Cristian, Oneata, Dan, Cucu, Horia, Burileanu, Corneliu, 2021 IEEE Spoken Language Technology Workshop (SLT), ISBN 978-1-7281-7066-4, 2021.
Digital Object Identifier: 10.1109/SLT48900.2021.9383577
[CrossRef]

Updated today

Disclaimer: All information displayed above was retrieved by using remote connections to respective databases. For the best user experience, we update all data by using background processes, and use caches in order to reduce the load on the servers we retrieve the information from. As we have no control on the availability of the database servers and sometimes the Internet connectivity may be affected, we do not guarantee the information is correct or complete. For the most accurate data, please always consult the database sites directly. Some external links require authentication or an institutional subscription.

Web of Science® is a registered trademark of Clarivate Analytics, Scopus® is a registered trademark of Elsevier B.V., other product names, company names, brand names, trademarks and logos are the property of their respective owners.


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