An Undecimated Wavelet-based Method for Cochlear Implant Speech Processing
Identifieur interne : 001448 ( Main/Merge ); précédent : 001447; suivant : 001449An Undecimated Wavelet-based Method for Cochlear Implant Speech Processing
Auteurs : Fatemeh Hajiaghababa ; Saeed Kermani ; Hamid R. MaratebSource :
- Journal of Medical Signals and Sensors [ 2228-7477 ] ; 2014.
Abstract
A cochlear implant is an implanted electronic device used to provide a sensation of hearing to a person who is hard of hearing. The cochlear implant is often referred to as a bionic ear. This paper presents an undecimated wavelet-based speech coding strategy for cochlear implants, which gives a novel speech processing strategy. The undecimated wavelet packet transform (UWPT) is computed like the wavelet packet transform except that it does not down-sample the output at each level. The speech data used for the current study consists of 30 consonants, sampled at 16 kbps. The performance of our proposed UWPT method was compared to that of infinite impulse response (IIR) filter in terms of mean opinion score (MOS), short-time objective intelligibility (STOI) measure and segmental signal-to-noise ratio (SNR). Undecimated wavelet had better segmental SNR in about 96% of the input speech data. The MOS of the proposed method was twice in comparison with that of the IIR filter-bank. The statistical analysis revealed that the UWT-based N-of-M strategy significantly improved the MOS, STOI and segmental SNR (
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PubMed: 25426428
PubMed Central: 4236803
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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">An Undecimated Wavelet-based Method for Cochlear Implant Speech Processing</title><author><name sortKey="Hajiaghababa, Fatemeh" sort="Hajiaghababa, Fatemeh" uniqKey="Hajiaghababa F" first="Fatemeh" last="Hajiaghababa">Fatemeh Hajiaghababa</name><affiliation><nlm:aff id="aff1"></nlm:aff></affiliation></author><author><name sortKey="Kermani, Saeed" sort="Kermani, Saeed" uniqKey="Kermani S" first="Saeed" last="Kermani">Saeed Kermani</name><affiliation><nlm:aff id="aff2"><italic>Department of Medical Physics and Medical Engineering, Isfahan University of Medical Sciences, Isfahan, Iran</italic></nlm:aff></affiliation></author><author><name sortKey="Marateb, Hamid R" sort="Marateb, Hamid R" uniqKey="Marateb H" first="Hamid R." last="Marateb">Hamid R. Marateb</name><affiliation><nlm:aff id="aff3"><italic>Department of Biomedical Engineering, Faculty of Engineering, University of Isfahan, Isfahan, Iran</italic></nlm:aff></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">25426428</idno><idno type="pmc">4236803</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4236803</idno><idno type="RBID">PMC:4236803</idno><date when="2014">2014</date><idno type="wicri:Area/Pmc/Corpus">002023</idno><idno type="wicri:Area/Pmc/Curation">002023</idno><idno type="wicri:Area/Pmc/Checkpoint">000E22</idno><idno type="wicri:Area/Ncbi/Merge">003472</idno><idno type="wicri:Area/Ncbi/Curation">003472</idno><idno type="wicri:Area/Ncbi/Checkpoint">003472</idno><idno type="wicri:Area/Main/Merge">001448</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">An Undecimated Wavelet-based Method for Cochlear Implant Speech Processing</title><author><name sortKey="Hajiaghababa, Fatemeh" sort="Hajiaghababa, Fatemeh" uniqKey="Hajiaghababa F" first="Fatemeh" last="Hajiaghababa">Fatemeh Hajiaghababa</name><affiliation><nlm:aff id="aff1"></nlm:aff></affiliation></author><author><name sortKey="Kermani, Saeed" sort="Kermani, Saeed" uniqKey="Kermani S" first="Saeed" last="Kermani">Saeed Kermani</name><affiliation><nlm:aff id="aff2"><italic>Department of Medical Physics and Medical Engineering, Isfahan University of Medical Sciences, Isfahan, Iran</italic></nlm:aff></affiliation></author><author><name sortKey="Marateb, Hamid R" sort="Marateb, Hamid R" uniqKey="Marateb H" first="Hamid R." last="Marateb">Hamid R. Marateb</name><affiliation><nlm:aff id="aff3"><italic>Department of Biomedical Engineering, Faculty of Engineering, University of Isfahan, Isfahan, Iran</italic></nlm:aff></affiliation></author></analytic><series><title level="j">Journal of Medical Signals and Sensors</title><idno type="eISSN">2228-7477</idno><imprint><date when="2014">2014</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p>A cochlear implant is an implanted electronic device used to provide a sensation of hearing to a person who is hard of hearing. The cochlear implant is often referred to as a bionic ear. This paper presents an undecimated wavelet-based speech coding strategy for cochlear implants, which gives a novel speech processing strategy. The undecimated wavelet packet transform (UWPT) is computed like the wavelet packet transform except that it does not down-sample the output at each level. The speech data used for the current study consists of 30 consonants, sampled at 16 kbps. The performance of our proposed UWPT method was compared to that of infinite impulse response (IIR) filter in terms of mean opinion score (MOS), short-time objective intelligibility (STOI) measure and segmental signal-to-noise ratio (SNR). Undecimated wavelet had better segmental SNR in about 96% of the input speech data. The MOS of the proposed method was twice in comparison with that of the IIR filter-bank. The statistical analysis revealed that the UWT-based N-of-M strategy significantly improved the MOS, STOI and segmental SNR (<italic>P</italic> < 0.001) compared with what obtained with the IIR filter-bank based strategies. The advantage of UWPT is that it is shift-invariant which gives a dense approximation to continuous wavelet transform. Thus, the information loss is minimal and that is why the UWPT performance was better than that of traditional filter-bank strategies in speech recognition tests. Results showed that the UWPT could be a promising method for speech coding in cochlear implants, although its computational complexity is higher than that of traditional filter-banks.</p></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Loizou, Pc" uniqKey="Loizou P">PC Loizou</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Loizou, Pc" uniqKey="Loizou P">PC Loizou</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Zeng, Fg" uniqKey="Zeng F">FG Zeng</name></author><author><name sortKey="Rebscher, S" uniqKey="Rebscher S">S Rebscher</name></author><author><name sortKey="Harrison, W" uniqKey="Harrison W">W Harrison</name></author><author><name sortKey="Sun, X" uniqKey="Sun X">X Sun</name></author><author><name sortKey="Feng, H" uniqKey="Feng H">H Feng</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Lopez Poveda, Ea" uniqKey="Lopez 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