Utilizing the neural networks for speech quality estimation based on the network characteristics
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F15%3A86096921" target="_blank" >RIV/61989100:27240/15:86096921 - isvavai.cz</a>
Alternative codes found
RIV/61989100:27240/16:86097972
Result on the web
<a href="http://www.springer.com/us/book/9783319272450" target="_blank" >http://www.springer.com/us/book/9783319272450</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-27247-4_9" target="_blank" >10.1007/978-3-319-27247-4_9</a>
Alternative languages
Result language
angličtina
Original language name
Utilizing the neural networks for speech quality estimation based on the network characteristics
Original language description
The paper deals with an issue of the speech quality estimation in Voice over IP technology under packet loss. Packet loss is a major problem for real-time Internet applications, 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. The general and RFC3611-compliant solution, which allows for quick and precise speech quality estimation without the need to analyzeor model the voice signal carried by the RTP (Real-time Transport Protocol) packets, is the contribution of this paper. The proposed solution is tested on G.711 A-law and further generalizes the already presented concepts of the speech quality estimation in the IP environment. The proposed approach of speech quality assessment belongs to non-intrusive methods and is based on the back-propagation neural networks.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2015
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Lecture Notes in Electrical Engineering. Volume 371
ISBN
978-3-319-27245-0
ISSN
1876-1100
e-ISSN
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Number of pages
11
Pages from-to
99-109
Publisher name
Springer
Place of publication
New York
Event location
Ho Chi Minh City
Event date
Dec 9, 2015
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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