Prediction of Speech Quality Based on Resilient Backpropagation Artificial Neural Network
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F17%3A10236467" target="_blank" >RIV/61989100:27240/17:10236467 - isvavai.cz</a>
Alternative codes found
RIV/61989100:27740/17:10236467
Result on the web
<a href="https://link.springer.com/article/10.1007/s11277-016-3746-2" target="_blank" >https://link.springer.com/article/10.1007/s11277-016-3746-2</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s11277-016-3746-2" target="_blank" >10.1007/s11277-016-3746-2</a>
Alternative languages
Result language
angličtina
Original language name
Prediction of Speech Quality Based on Resilient Backpropagation Artificial Neural Network
Original language description
The paper presents a system for monitoring and assessment the speech quality in the IP telephony infrastructures using modular probes. The probes are placed at key nodes in the network where aggregating packet loss data. The system dynamically measures speech quality and results are collected on a central server. For data analysis we applied four-state Markov model for modeling the impact of network impairments on speech quality, afterwards, the resilient back propagation (Rprop) algorithm was used to train a neural network. Information about the speech quality are displayed in the form of automatically generated graphs and tables. The proposed solution has been tested with selected codecs and further generalizes the already presented concepts of the speech quality estimation in the IP environment.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
20203 - Telecommunications
Result continuities
Project
—
Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Wireless Personal Communications
ISSN
0929-6212
e-ISSN
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Volume of the periodical
96
Issue of the periodical within the volume
4
Country of publishing house
US - UNITED STATES
Number of pages
15
Pages from-to
5375-5389
UT code for WoS article
000411881300025
EID of the result in the Scopus database
2-s2.0-84990843631