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  • 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 the impact on speech quality was carried out by an intrusive objective algorithm Perceptual Evaluation of Speech Quality (PESQ). DWT and SWT transformation was applied to voice samples that were devalued by Gaussian white noise. Afterwards, we determined the effectiveness of DWT and SWT by means of objective algorithm PESQ. The decisive criterion for determining the quality of a voice sample once the noise had been removed was Mean Opinion Score (MOS) which we obtained in PESQ. The contribution of this work lies in the evaluation of efficiency of wavelet transformation to suppress noise in voice samples.
  • 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 the impact on speech quality was carried out by an intrusive objective algorithm Perceptual Evaluation of Speech Quality (PESQ). DWT and SWT transformation was applied to voice samples that were devalued by Gaussian white noise. Afterwards, we determined the effectiveness of DWT and SWT by means of objective algorithm PESQ. The decisive criterion for determining the quality of a voice sample once the noise had been removed was Mean Opinion Score (MOS) which we obtained in PESQ. The contribution of this work lies in the evaluation of efficiency of wavelet transformation to suppress noise in voice samples. (en)
Title
  • Analysis and removing noise from the speech signal using wavelet transforms
  • Analysis and removing noise from the speech signal using wavelet transforms (en)
skos:prefLabel
  • Analysis and removing noise from the speech signal using wavelet transforms
  • Analysis and removing noise from the speech signal using wavelet transforms (en)
skos:notation
  • RIV/61989100:27240/13:86086896!RIV14-MSM-27240___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • V
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 60461
http://linked.open...ai/riv/idVysledku
  • RIV/61989100:27240/13:86086896
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • SWT; speech quality; PESQ; MOS; Gaussian white noise; DWT (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [65741622BE11]
http://linked.open...v/mistoKonaniAkce
  • Baltimore
http://linked.open...i/riv/mistoVydani
  • Bellingham
http://linked.open...i/riv/nazevZdroje
  • Proceedings of SPIE - The International Society for Optical Engineering. Volume 8750
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Tomala, Karel
  • Vozňák, Miroslav
  • Řezáč, Filip
  • Šafařík, Jakub
  • Partila, Pavol
http://linked.open...vavai/riv/typAkce
http://linked.open...ain/vavai/riv/wos
  • 000324809400011
http://linked.open.../riv/zahajeniAkce
issn
  • 0277-786X
number of pages
http://bibframe.org/vocab/doi
  • 10.1117/12.2015722
http://purl.org/ne...btex#hasPublisher
  • SPIE
https://schema.org/isbn
  • 978-0-8194-9541-9
http://localhost/t...ganizacniJednotka
  • 27240
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