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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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  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
 
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Download PDF pdficon (856 KB) | Citation | Downloads: 1,012 | Views: 3,970

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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Full text preview
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%.


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

[1] C. Vaquero, O. Saz, W. Rodriguez, E. Lleida, "Human Language Technologies for Speech Therapy in Spanish Language", [Online] Available: Temporary on-line reference link removed - see the PDF document

[2] G. Potamianos, C. Neti, "Automatic Speechreading of Impaired Speech", in Proceedings of the Audio-Visual Speech Processing Workshop, Scheelsminde, Denmark, 2001.

[3] T. Starner, J. Weaver, A. Pentland, "Real-Time American Sign Language Recognition Using Desk and Wearable Computer Based Video", in IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 20, no. 12, december 1998, pp. 1371 - 1375.
[CrossRef] [Web of Science Times Cited 696] [SCOPUS Times Cited 957]


[4] N. Moustroufas, V.Digalakis, "Automatic Pronunciation Evaluation of Foreign Speakers Using Unknown Text". [Online] Available: Temporary on-line reference link removed - see the PDF document

[5] V. Young, A. Mihailidis, "Difficulties in Automatic Speech Recognition of Dysarthric Speakers and Implications for Speech-Based Applications Used by the Elderly: A Literature Review", in Assistive Technology: The Official Journal of RESNA, 2010, Vol.22, Issue 2, pp. 99-112.
[CrossRef] [Web of Science Times Cited 96] [SCOPUS Times Cited 120]


[6] S. G. Pentiuc, I. Tobolcea, O. A. Schipor, M. Danubianu, D. M. Schipor, "Translation of the Speech Therapy Programs in the Logomon Assisted Therapy System," Advances in Electrical and Computer Engineering, vol. 10, no. 2, pp. 48-52, 2010.
[CrossRef] [Full Text] [Web of Science Times Cited 12] [SCOPUS Times Cited 15]


[7] O. A. Schipor, S.-G. Pentiuc, M.D. Schipor, "Improving Computer Based Speech Therapy Using a Fuzzy Expert System", in Computing and Informatics, Vol. 22, 2003. [Online] Available: Temporary on-line reference link removed - see the PDF document

[8] M. Danubianu, S.-G. Pentiuc, O.A. Schipor, M. Nestor, I. Ungureanu, "Distributed Intelligent System for Personalized Therapy of Speech Disorders", in The Third International Multi-Conference on Computing in the Global Information Technology, 2008, Athens, Greece.

[9] Gladiola Andruseac, H. Costin, C. Rotariu, "eLearning Platform for Rehabilitation of the Romanian Patients with Neurological Diseases," in Proc. of ICIW 2009, Fourth Int. Conf. on Internet and Web Applications and Services, Venice, Italy, May 2009, pp.573-577, ISBN: 978-0-7695-3613-2

[10] Gladiola Andruseac, H. Costin, C. Rotariu, "Design of a Virtual Learning Environmnent for Romanian Patients with Dyslexia" in Proc. of 1st International Conference on Computer Supported Education, CSEDU 2009, 23-26 March 2009, Lisbon, Portugal, vol. II, pp. 301-304, ISBN: 978-989-8111-83-8

[11] O. Grigore, C. Grigore, V. Velican, "Intelligent System for Impaired Speech Evaluation", in Proceedings of the International Conference on Circuits, Systems, Signals, 10/2010, pp. 365-368. [Online] Available: Temporary on-line reference link removed - see the PDF document

[12] O. Grigore, C. Grigore, V. Velican, "Impaired Speech Evaluation using Mel-Cepstrum Analysis", in International Journal Of Circuits, Systems And Signal Processing, pp. 70-77. [Online] Available: Temporary on-line reference link removed - see the PDF document

[13] O. Grigore, V. Velican, "Pattern Recognition Based Method Used in Identifying Impaired Speech", in Proceedings of the 2nd International Conference on Applied Informatics and Computing Theory (AICT '11): Recent Researches in Applied Informatics, 2011, Prague - Czech Republic, pp. 190-194, [Online] Available: Temporary on-line reference link removed - see the PDF document

[14] I. Gavat, O. Grigore, V. Velican, " Impaired Speech Recognition. Case Study: Recognition of Initial 'r' Consonant in Rhotacsim Affected Pronunciations", in Proceedings of the 6th Conference on Speech Technology and Human-Computer Dialogue (SpeD), 2011, Brasov, Romania, pp.1-6.

[15] O. Grigore, V. Velican, "Self-Organizing Maps for Identifying Impaired Speech", in Advances in Electrical and Computer Engineering, 2011, Vol. 11, Issue 3, pp.41 - 48.

[16] D. V. Popovici, C. Buica-Belciu, V.Velican, "From ASR to CAST: Intelligent Systems for the Diagnosis and Therapy of Speech-Language Disorders", in Revista de Psihopedagogie, 2010, Issue 2, pp.25-37.

[17] P. Popescu-Neveanu, Psychology Dictionary, ed: Albatros, Bucuresti, 1976.

[18] D. V. Popovici, C. Buica-Belciu, A. Iordan, "Phonetic Particularities of Dyslalic Children Pronunciations", in O Scoala Deschisa, 2/2009, Ed.SS6SN, pp. 116-124.

[19] E. Verza, Dyslalia and its Therapy, E.D.P., Bucuresti, 1977

[20] I. Gavat, M. Zirra, O. Grigore et al, Fundamentals of Speech Synthesis, Ed. Printech, Bucuresti, 2000.

[21] C. Paunescu et al., An Introduction in Logophedics, Bucuresti, 1976

[22] R. Tallia, P. Morello, G. Castellano, "The Walsh-Hadamard Transform: An Alternative Means of Obtaining Phase and Amplitude Maps", in The Journal of Nulcear Medicine, 1984, Vol.25, Issue 5, pp.608-612. [Online] Available: Temporary on-line reference link removed - see the PDF document

[23] X. Wu, V. Kumar, J. R. Quinlan et al. "Top 10 Algorithms in Data Mining" - survey paper, 2007.

[24] T.-.H. Cho, R. Conners, P. Araman, "A Comparison of Rule-Based, K-Nearest Neighbor, and Neural Net Classifiers for Automated Industrial Inspection", in Proceedings of the IEEE/ACM International Conference on Developing and Managing Expert System Programs, 1991, Washington, USA, pp. 202 - 209.

[25] L. Baoli, Y. Shiwen, L. Qin, "An Improved k-Nearest Neighbour Algorithm for Text Categorization", [Online] Available: Temporary on-line reference link removed - see the PDF document

[26] W. Wang, S. Li, C. Wang, ICL at NTCIR-7: "An Improved KNN Algorithm for Text Categorization", in Proceedings of NTCIR-7 Workshop Meeting, 2008, Tokyo, Japan, pp.385-388.[Online] Available: Temporary on-line reference link removed - see the PDF document

[27] R. Hassan, M. Hossain, J. Bailey, "Improving k-Nearest Neighbour Classification with Distance Functions Based on Receiver Operating Characteristics", in Proceedings of the 2008 European Conference on Machine Learning and Knowledge Discovery in Databases, 2008, Berlin, Germany, pp.489 - 504.
[CrossRef] [SCOPUS Times Cited 19]


References Weight

Web of Science® Citations for all references: 804 TCR
SCOPUS® Citations for all references: 1,111 TCR

Web of Science® Average Citations per reference: 30 ACR
SCOPUS® Average Citations per reference: 41 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 2024-11-21 06:40 in 30 seconds.




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Stefan cel Mare University of Suceava, Romania


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