Utilizing the neural networks for speech quality estimation based on the network characteristics

Kód výsledku v 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>

Nalezeny alternativní kódy

RIV/61989100:27240/16:86097972

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

Utilizing the neural networks for speech quality estimation based on the network characteristics

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Utilizing the neural networks for speech quality estimation based on the network characteristics

Popis výsledku anglicky

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.

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2015

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Lecture Notes in Electrical Engineering. Volume 371

ISBN

978-3-319-27245-0

ISSN

1876-1100

e-ISSN

—

Počet stran výsledku

11

Strana od-do

99-109

Název nakladatele

Springer

Místo vydání

New York

Místo konání akce

Ho Chi Minh City

Datum konání akce

9. 12. 2015

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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