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JCR Impact Factor: 0.595
JCR 5-Year IF: 0.661
Issues per year: 4
Current issue: Nov 2017
Next issue: Feb 2018
Avg review time: 106 days


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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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LATEST NEWS

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.

2017-Apr-04
We have the confirmation Advances in Electrical and Computer Engineering will be included in the EBSCO database.

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.

2017-Jan-30
We have the confirmation Advances in Electrical and Computer Engineering will be included in the Gale database.

2016-Dec-17
IoT is a new emerging technology domain which will be used to connect all objects through the Internet for remote sensing and control. IoT uses a combination of WSN (Wireless Sensor Network), M2M (Machine to Machine), robotics, wireless networking, Internet technologies, and Smart Devices. We dedicate a special section of Issue 2/2017 to IoT. Prospective authors are asked to make the submissions for this section no later than the 31st of March 2017, placing "IoT - " before the paper title in OpenConf.

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  2/2017 - 11

Speech Rate Control for Improving Elderly Speech Recognition of Smart Devices

SON, G. See more information about SON, G. on SCOPUS See more information about SON, G. on IEEExplore See more information about SON, G. on Web of Science, KWON, S. See more information about  KWON, S. on SCOPUS See more information about  KWON, S. on SCOPUS See more information about KWON, S. on Web of Science, LIM, Y. See more information about LIM, Y. on SCOPUS See more information about LIM, Y. on SCOPUS See more information about LIM, Y. 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 (1,769 KB) | Citation | Downloads: 133 | Views: 218

Author keywords
automatic speech recognition, human computer interaction, speech analysis, man machine systems, human factor

References keywords
speech(15), time(4), communication(4), aging(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2017-05-31
Volume 17, Issue 2, Year 2017, On page(s): 79 - 84
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2017.02011
Web of Science Accession Number: 000405378100011
SCOPUS ID: 85020117598

Abstract
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Although smart devices have become a widely-adopted tool for communication in modern society, it still requires a steep learning curve among the elderly. By introducing a voice-based interface for smart devices using voice recognition technology, smart devices can become more user-friendly and useful to the elderly. However, the voice recognition technology used in current devices is attuned to the voice patterns of the young. Therefore, speech recognition falters when an elderly user speaks into the device. This paper has identified that the elderly's improper speech rate by each syllable contributes to the failure in the voice recognition system. Thus, upon modifying the speech rate by each syllable, the voice recognition rate saw an increase of 12.3%. This paper demonstrates that by simply modifying the speech rate by each syllable, which is one of the factors that causes errors in voice recognition, the recognition rate can be substantially increased. Such improvements in voice recognition technology can make it easier for the elderly to operate smart devices that will allow them to be more socially connected in a mobile world and access information at their fingertips. It may also be helpful in bridging the communication divide between generations.


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

[1] Korea National Statistic office. "Social Survey; Welfare Category; Difficulties Experienced by Senior Citizens, Official Statistics Research Newsletter, vol.5, pp.2-3, 2013.

[2] W. S. Kang, M. S. Kim, J. W. Ko, "Effects of the smartphone information use and performance on life satisfaction among the elderly," Korean Gerontological Society, vol.33, no.1, pp.199-214, 2013.

[3] B. C. Sonies, "Oral-motor Problems," Communication Disorders in Aging: Assessment and Management, Washington, Gallaudet University Press, pp. 185-213, 1987.

[4] J. W. Bennett, P. H. H. M. Van Lieshout, C. M. Steele, "Tongue control for speech and swallowing in healthy younger and older subjects," International Journal of Orofacial Myology," vol.33, pp.5–18, 2007.

[5] J. C. Kahane, "Anatomic and physiologic changes in the aging peripheral speech mechanism," Aging: Communication processes and disorders, pp.21-45, 1981.

[6] S. Y. Lee, "The overall speaking rate and articulation rate of normal elderly people," Graduate program in speech and language pathology, Master these, Yonsei University, 2011.

[7] W. J. Ryan, J.William, "Acoustic aspects of the aging voice", Journal of Gerontology, vol.27, no.2, pp.265-268, 1972.
[CrossRef]


[8] Y. H. Kim. "Geriatric speech. plenary session IV," Yonsei University College of Medicine, Otolaryngology clinic. pp.205-207, 2003.

[9] W. H. Manning, K. L. Monte, "Fluency breaks in older speakers: implications for a model of stuttering throughout the life cycle," Journal of fluency disorders. Vol.6, no.1, pp.35–48, 1981.
[CrossRef] [Web of Science Times Cited 11] [SCOPUS Times Cited 14]


[10] J. D. Harnsberger, R. Shrivastav, R. Brown, W.S. Rothman, H. Hollien, "Speaking rate and fundamental frequency as speech cues to perceived age," Journal of voice, vol.22, no.1, pp.58-69, 2008.
[CrossRef] [Web of Science Times Cited 29] [SCOPUS Times Cited 57]


[11] H. Y. Pyo, H. S. Shim, "Paralytic disorder words (dysarthria) for improving the clarity of research trends: A Literature Review," Special Education, vol.4, no.1, pp.35-50, 2005

[12] M. Richardson, M. Hwang, A, Acero, X.Huang, "Improvements on speech recognition for fast talkers," Eurospeech, pp.411-414, 1999.

[13] S. Kwon, S. Kim, J. Choeh. "Preprocessing for elderly speech recognition of smart devices," Computer Speech & Language. vol.36, pp.110-121, 2016.
[CrossRef] [Web of Science Times Cited 1] [SCOPUS Times Cited 1]


[14] A. Aniruddha, M. Mathew, S. Amantula, C. Sekhar, "Gammatone wavelet Cepstral Coefficients for robust speech recognition," TENCON 2013, pp.1-4, 2013.
[CrossRef] [SCOPUS Times Cited 5]


[15] W. Verhelst, M. Roelands, "An overlap-add technique based on waveform similarity (WSOLA) for high quality time-scale modification of speech," Acoustics, Speech, and Signal Processing(ICASSP), vol.2, pp. 554-557, 1993.
[CrossRef]


[16] W. Verhelst, "Overlap-add methods for time-scaling of speech. Speech Communication," vol.30, no.4, pp.207-221, 2000.
[CrossRef] [SCOPUS Times Cited 39]


[17] C. d'Alessandro, "Time-frequency speech transformation based on an elementary waveform representation. Speech communication," pp.419-431, 1990.
[CrossRef] [Web of Science Times Cited 6] [SCOPUS Times Cited 5]


[18] D. Henja, B. Musicus "The solafs time-scale modification algorithm," Technical Report of BBN, 1991.

[19] S. Kwon, "Voice-driven sound effect manipulation," International Journal of Human-Computer Interaction, pp.373–382, 2012.
[CrossRef] [Web of Science Times Cited 3] [SCOPUS Times Cited 3]


[20] S. Dusan, L.R. Rabiner, "On the relation between maximum spectral transition positions and phone boundaries," INTERSPEECH, pp.17-21, 2006.
[CrossRef] [Web of Science Times Cited 3] [SCOPUS Times Cited 4]




References Weight

Web of Science® Citations for all references: 53 TCR
SCOPUS® Citations for all references: 128 TCR

Web of Science® Average Citations per reference: 3 ACR
SCOPUS® Average Citations per reference: 6 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 13:24 in 72 seconds.




Note1: Web of Science® is a registered trademark of Thomson Reuters.
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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania


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