Parametric audio quality estimation models for broadcasting systems and web-casting applications based on the Genetic Programming
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- @InProceedings{Jakubik:2020:ICETA,
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author = "M. Jakubik and P. Pocta",
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title = "Parametric audio quality estimation models for
broadcasting systems and web-casting applications based
on the Genetic Programming",
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booktitle = "2020 18th International Conference on Emerging
eLearning Technologies and Applications (ICETA)",
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year = "2020",
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pages = "219--225",
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month = nov,
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keywords = "genetic algorithms, genetic programming, Performance
evaluation, Electronic learning, Education, Estimation,
Broadcasting, Parametric statistics",
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DOI = "doi:10.1109/ICETA51985.2020.9379251",
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abstract = "The COVID-19 pandemic has been one of the biggest
disruptions to education that the world has ever
experienced, affecting the most of the world student
population. Many countries turned to online based
distance education to ensure that learning never stops.
As a consequence, throughout the globe there has been
an increasing trend among the students to use different
broadcasting systems and web-casting applications for
the purpose of online learning. However, the video or
audio quality that these various applications offer
will be the key factor for their acceptance, i.e.
whether or not the students will be willing to use
those systems for online learning. Therefore, a machine
learning technique, i.e. Genetic Programming, is used
in this work for the purpose of assessing audio quality
using an objective approach. A design and performance
evaluation of the parametric models estimating the
audio quality perceived by the end user of broadcasting
systems and web-casting applications are presented in
this paper. To estimate the quality of audio
broadcasting systems and web-casting applications, a
set of parameters influencing the quality is used as an
input for the developed parametric quality estimation
models. The results obtained by the developed
parametric audio quality estimation models have
validated Genetic Programming as a powerful technique,
providing a good accuracy and generalization
capabilities. This makes it a possible candidate for
the estimation of audio quality perceived by the end
user in the context of the broadcasting systems and
web-casting applications.",
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notes = "Also known as \cite{9379251}",
- }
Genetic Programming entries for
Martin Jakubik
Peter Pocta
Citations