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dc.contributor.authorAlatwi, Aadel
dc.contributor.authorSo, Stephen
dc.contributor.authorPaliwal, Kuldip
dc.contributor.editorChristopher Carignan, Michael D. Tyler
dc.date.accessioned2017-09-13T00:29:25Z
dc.date.available2017-09-13T00:29:25Z
dc.date.issued2016
dc.identifier.urihttp://hdl.handle.net/10072/100785
dc.description.abstractIn this paper, we propose a perceptually-motivated method for modifying the speech power spectrum to obtain a set of linear prediction coding (LPC) parameters that possess good noiserobustness properties in network speech recognition. Speech recognition experiments were performed to compare the accuracy obtained from MFCC features extracted from AMR-coded speech that use these modified LPC parameters, as well as from LPCCs extracted from AMR bitstream parameters. The results show that when using the proposed LP analysis method, the recognition performance was on average 1.2% - 6.1% better than when using the conventional LP method, depending on the recognition task.
dc.description.peerreviewedYes
dc.languageEnglish
dc.publisherAustralasian Speech Science & Technology Association
dc.publisher.placeAustralia
dc.publisher.urihttp://www.assta.org/?q=sst-conferences
dc.relation.ispartofconferencenameSST2016
dc.relation.ispartofconferencetitleProceedings of the Sixteenth Australasian International Conference on Speech Science and Technology
dc.relation.ispartofdatefrom2016-12-06
dc.relation.ispartofdateto2016-12-09
dc.relation.ispartoflocationSydney, Australia
dc.subject.fieldofresearchSignal Processing
dc.subject.fieldofresearchcode090609
dc.titleNoise-robust linear prediction cepstral features for network speech recognition
dc.typeConference output
dc.type.descriptionE1 - Conferences
dc.type.codeE - Conference Publications
dc.description.versionVersion of Record (VoR)
gro.facultyGriffith Sciences, Griffith School of Engineering
gro.rights.copyright© 2016 ASSTA. The attached file is reproduced here in accordance with the copyright policy of the publisher. Please refer to the conference's website for access to the definitive, published version.
gro.hasfulltextFull Text
gro.griffith.authorPaliwal, Kuldip K.
gro.griffith.authorSo, Stephen
gro.griffith.authorAlatwi, Aadel MA.


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