IEEE Consumer Electronics Magazine - March/April 2021 - 42

Smart Computing

environment noises, which discourages people
from using these devices. Also, this system works
with lower CPU consumption and lower processing time (666 ms) compared with other architecture. Therefore, this developed system can help
the further development of a noise removal system
that is suitable for a modern smartphone.

11. J. Six, Digital Sound Processing and Java-
Documentation for the TarsosDSP Audio Processing
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USA, 2020.
13. J. Lemley and P. Corcoran, " Deep learning for
consumer devices and services 4-A review of

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Winner Roedily's research interests include audio
signal processing and mobile devices. He is currently
working toward the M.S. degree in electronic and
computer engineering with the Department of Electronic and Computer Engineering, National Taiwan
University of Science and Technology, Taipei,
Taiwan. Contact him at roedilywinner@gmail.com.
Shanq-Jang Ruan received the Ph.D. degree in
electrical engineering from National Taiwan University,
Taipei in 2002. He is currently a distinguished professor with the Department of Electronic and Computer
Engineering, National Taiwan University of Science
and Technology, Taipei, Taiwan. His research interests
include embedded deep neural network processing,
energy-efficient image processing, and embedded
system design. He is the corresponding author of this
article. Contact him at sjruan@mail.ntust.edu.tw.
Lieber Po-Hung Li received the Ph.D. degree in
clinical medicine from National Yang-Ming University,
Taipei in 2006. He is currently with the Department of
Otolaryngology, Cheng-Hsin General Hospital, Taipei,
Taiwan. He is also a teacher with the Faculty of Medicine, School of Medicine, National Yang-Ming University, Taipei, and involved in research works with the
Department of Medical Research, China Medical University, Taichung, Taiwan. His research interests
include clinical imaging and central auditory plasticity
of MEG signals. Contact him at phli@gm.ym.edu.tw.

ACM Int. Conf. Multimedia, 2014, pp. 1041-1044.
10. J. Singh and R. Joshi, " Background sound
classification in speech audio segments, " in Proc. Int.
Conf. Speech Technol. Human-Comput. Dialogue,
2019, pp. 1-6.

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IEEE Consumer Electronics Magazine
https://www.who.int/news-room/fact-sheets/detail/deafness-and-hearing-loss https://www.who.int/news-room/fact-sheets/detail/deafness-and-hearing-loss https://www.github.com/WinRoedily/Mobile_Noise_Classifier https://www.github.com/WinRoedily/Mobile_Noise_Classifier
IEEE Consumer Electronics Magazine - March/April 2021

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