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Cue estimation for vowel perception prediction in low signal-to-noise ratios

Dissertation (MEng)--University of Pretoria, 2009.

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Other Authors: Hanekom, J.J. (Johannes Jurgens)
Format: Thesis
Published: University of Pretoria 2013
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access_status_str Open Access
author2 Hanekom, J.J. (Johannes Jurgens)
author_browse Hanekom, J.J. (Johannes Jurgens)
author_facet Hanekom, J.J. (Johannes Jurgens)
collection Thesis
dc_rights_str_mv © 2008, University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria
description Dissertation (MEng)--University of Pretoria, 2009.
format Thesis
id oai:repository.up.ac.za:2263/24619
institution University of Pretoria (South Africa)
last_indexed 2026-06-10T12:39:34.197Z
license_str Other — see source repository
provenance_str_mv Harvested via OAI-PMH from UPSpace — University of Pretoria Institutional Repository
publishDate 2013
publishDateRange 2013
publishDateSort 2013
publisher University of Pretoria
publisherStr University of Pretoria
record_format dspace
source_str UPSpace — University of Pretoria Institutional Repository
spelling oai:repository.up.ac.za:2263/24619 Cue estimation for vowel perception prediction in low signal-to-noise ratios Hanekom, J.J. (Johannes Jurgens) bburmeister@csir.co.za Burmeister, Brian Low signal to-noise ratio Speech cue estimation Speech enhancement Hearing perception model Gehoorpersepsiemodel Spraakkwaliteitverbetering Spraakeienskapberaming Lae sein-tot-ruis UCTD Dissertation (MEng)--University of Pretoria, 2009. This study investigates the signal processing required in order to allow for the evaluation of hearing perception prediction models at low signal-to-noise Ratios (SNR). It focusses on speech enhancement and the estimation of the cues from which speech may be recognized, specifically where these cues are estimated from severely degraded speech (SNR ranging from -10 dB to -3 dB). This research has application in the field of cochlear implants (CI), where a listener would hear degraded speech due to several distortions introduced by the biophysical interface (e.g. frequency and amplitude discretization). These difficulties can also be interpreted as a loss in signal quality due to a specific type of noise. The ability to investigate perception in low SNR conditions may have application in the development of CI signal processing algorithms to counter the effects of noise. In the military domain a speech signal may be degraded intentionally by enemy forces or unintentionally owing to engine noise, for example. The ability to analyse and predict perception can be used for algorithm development to counter the unintentional or intentional interference or to predict perception degradation if low SNR conditions cannot be avoided. A previously documented perception model (Svirsky, 2000) is used to illustrate that the proposed signal processing steps can indeed be used to estimate the various cues used by the perception model at SNRs successfully as low as -10 dB. AFRIKAANS : Hierdie studie ondersoek die seinprosessering wat nodig is om ’n gehoorpersepsievoorspellingmodel te evalueer by lae sein-tot-ruis-verhoudings. Hierdie studie fokus op spraakverbetering en die estimasie van spraakeienskappe wat gebruik kan word tydens spraakherkenning, spesifiek waar hierdie eienskappe beraam word vir ernstig gedegradeerde spraak (sein-tot-ruisverhoudings van -10 dB tot -3 dB). Hierdie navorsing is van toepassing in die veld van kogleêre inplantings, waar die luisteraar degradering van spraak ervaar weens die bio-fisiese koppelvlak (bv. diskrete frekwensie en amplitude). Hierdie degradering kan gesien word as ’n verlies aan seinkwaliteit weens ’n spesifieke tipe ruis. Die vermoë om persepsie te ondersoek by lae sein-tot-ruis kan toegepas word tydens die ontwikkeling van kogleêre inplantingseinprosesseringalgoritmes om die effekte van ruis teen te werk. In die militêre omgewing kan spraak deur vyandige magte gedegradeer word, of degradering van spraak kan plaasvind as gevolg van bv. enjingeraas. Die vermoë om persepsie te ondersoek en te voorspel in die teenwoordigheid van ruis kan gebruik word vir algoritme-ontwikkeling om die ruis teen te werk of om die verlies aan persepsie te voorspel waar lae sein-tot-ruis verhoudings nie vermy kan word nie. ’n Voorheen gedokumenteerde persepsiemodel (Svirsky, 2000) word gebruik om te demonstreer dat die voorgestelde seinprosesseringstappe wel suksesvol gebruik kan word om die spraakeienskappe te beraam wat deur die persepsiemodel benodig word by sein-tot-ruis verhouding so laag as -10 dB. Copyright Electrical, Electronic and Computer Engineering unrestricted 2013-09-06T18:05:25Z 2009-05-18 2013-09-06T18:05:25Z 2009-04-15 2009-05-15 2009-05-13 Dissertation Burmeister, B 2008, Cue estimation for vowel perception prediction in low signal-to-noise ratios, MEng dissertation, University of Pretoria, Pretoria, viewed yymmdd < http://hdl.handle.net/2263/24619 > E1294/gm http://hdl.handle.net/2263/24619 http://upetd.up.ac.za/thesis/available/etd-05132009-151828/ © 2008, University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria application/pdf University of Pretoria
spellingShingle Low signal to-noise ratio
Speech cue estimation
Speech enhancement
Hearing perception model
Gehoorpersepsiemodel
Spraakkwaliteitverbetering
Spraakeienskapberaming
Lae sein-tot-ruis
UCTD
Cue estimation for vowel perception prediction in low signal-to-noise ratios
title Cue estimation for vowel perception prediction in low signal-to-noise ratios
title_full Cue estimation for vowel perception prediction in low signal-to-noise ratios
title_fullStr Cue estimation for vowel perception prediction in low signal-to-noise ratios
title_full_unstemmed Cue estimation for vowel perception prediction in low signal-to-noise ratios
title_short Cue estimation for vowel perception prediction in low signal-to-noise ratios
title_sort cue estimation for vowel perception prediction in low signal to noise ratios
topic Low signal to-noise ratio
Speech cue estimation
Speech enhancement
Hearing perception model
Gehoorpersepsiemodel
Spraakkwaliteitverbetering
Spraakeienskapberaming
Lae sein-tot-ruis
UCTD
url http://hdl.handle.net/2263/24619
http://upetd.up.ac.za/thesis/available/etd-05132009-151828/