Analysis and removing noise from the speech signal using wavelet transforms

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F13%3A86086896" target="_blank" >RIV/61989100:27240/13:86086896 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1117/12.2015722" target="_blank" >http://dx.doi.org/10.1117/12.2015722</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1117/12.2015722" target="_blank" >10.1117/12.2015722</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Analysis and removing noise from the speech signal using wavelet transforms

Popis výsledku v původním jazyce

The paper discusses the use of Discrete Wavelet Transform (DWT) and Stationary Wavelet Transform (SWT) wavelet in removing noise from voice samples and evaluation of its impact on speech quality. One significant part of Quality of Service (QoS) in communication technology is the speech quality assessment. However, this part is seriously overlooked as telecommunication providers often focus on increasing network capacity, expansion of services offered and their enforcement in the market. Among the fundamental factors affecting the transmission properties of the communication chain is noise, either at the transmitter or the receiver side. A wavelet transform (WT) is a modern tool for signal processing. One of the most significant areas in which wavelet transforms are used is applications designed to suppress noise in signals. To remove noise from the voice sample in our experiment, we used the reference segment of the voice which was distorted by Gaussian white noise. An evaluation of th

Název v anglickém jazyce

Analysis and removing noise from the speech signal using wavelet transforms

Popis výsledku anglicky

The paper discusses the use of Discrete Wavelet Transform (DWT) and Stationary Wavelet Transform (SWT) wavelet in removing noise from voice samples and evaluation of its impact on speech quality. One significant part of Quality of Service (QoS) in communication technology is the speech quality assessment. However, this part is seriously overlooked as telecommunication providers often focus on increasing network capacity, expansion of services offered and their enforcement in the market. Among the fundamental factors affecting the transmission properties of the communication chain is noise, either at the transmitter or the receiver side. A wavelet transform (WT) is a modern tool for signal processing. One of the most significant areas in which wavelet transforms are used is applications designed to suppress noise in signals. To remove noise from the voice sample in our experiment, we used the reference segment of the voice which was distorted by Gaussian white noise. An evaluation of th

Druh

D - Stať ve sborníku

CEP obor

JA - Elektronika a optoelektronika, elektrotechnika

OECD FORD obor

—

Projekt

—

Návaznosti

V - Vyzkumna aktivita podporovana z jinych verejnych zdroju

Rok uplatnění

2013

Kód důvěrnosti údajů

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

Název statě ve sborníku

Proceedings of SPIE - The International Society for Optical Engineering. Volume 8750

ISBN

978-0-8194-9541-9

ISSN

0277-786X

e-ISSN

—

Počet stran výsledku

8

Strana od-do

"87500D", 1-8

Název nakladatele

SPIE

Místo vydání

Bellingham

Místo konání akce

Baltimore

Datum konání akce

1. 5. 2013

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000324809400011