Title page for ETD etd-05132009-151828


Document Type Master's Dissertation
Author Burmeister, Brian
URN etd-05132009-151828
Document Title Cue estimation for vowel perception prediction in low signal-to-noise ratios
Degree MEng
Department Electrical, Electronic and Computer Engineering
Supervisor
Advisor Name Title
Prof J J Hanekom Supervisor
Keywords
  • low signal to-noise ratio
  • speech cue estimation
  • speech enhancement
  • hearing perception model
  • gehoorpersepsiemodel
  • spraakkwaliteitverbetering
  • spraakeienskapberaming
  • lae sein-tot-ruis
Date 2009-04-15
Availability unrestricted
Abstract
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 ín 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 kogleÍre inplantings, waar die luisteraar degradering van spraak ervaar weens die bio-fisiese koppelvlak (bv. diskrete frekwensie en amplitude). Hierdie degradering kan gesien word as ín verlies aan seinkwaliteit weens ín spesifieke tipe ruis. Die vermoŽ om persepsie te ondersoek by lae sein-tot-ruis kan toegepas word tydens die ontwikkeling van kogleÍre inplantingseinprosesseringalgoritmes om die effekte van ruis teen te werk. In die militÍre omgewing kan spraak deur vyandige magte gedegradeer word, of degradering van spraak kan plaasvind as gevolg van bv. enjingeraas. Die vermoŽ 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. ín 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 © 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

Please cite as follows:

Burmeister, B 2008, Cue estimation for vowel perception prediction in low signal-to-noise ratios, MEng dissertation, University of Pretoria, Pretoria, viewed yymmdd < http://upetd.up.ac.za/thesis/available/etd-05132009-151828 / >

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