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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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  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
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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

[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] [SCOPUS Times Cited 63]

[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 12] [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 77] [SCOPUS Times Cited 87]

[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 5] [SCOPUS Times Cited 11]

[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 22]

[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.

[16] W. Verhelst, "Overlap-add methods for time-scaling of speech. Speech Communication," vol.30, no.4, pp.207-221, 2000.
[CrossRef] [Web of Science Times Cited 36] [SCOPUS Times Cited 51]

[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 8]

[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 4] [SCOPUS Times Cited 5]

References Weight

Web of Science® Citations for all references: 143 TCR
SCOPUS® Citations for all references: 264 TCR

Web of Science® Average Citations per reference: 7 ACR
SCOPUS® Average Citations per reference: 13 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 2021-10-13 20:25 in 68 seconds.

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