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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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Clarivate Analytics published the InCites Journal Citations Report for 2017. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.699, and the JCR 5-Year Impact Factor is 0.674.

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.

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.

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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 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 (1,769 KB) | Citation | Downloads: 252 | Views: 828

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

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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

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References Weight

Web of Science® Citations for all references: 102 TCR
SCOPUS® Citations for all references: 214 TCR

Web of Science® Average Citations per reference: 5 ACR
SCOPUS® Average Citations per reference: 10 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 2019-04-19 10:54 in 75 seconds.

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