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dc.contributor.authorSchwerin, B
dc.contributor.authorSo, Stephen
dc.date.accessioned2019-05-02T23:58:11Z
dc.date.available2019-05-02T23:58:11Z
dc.date.issued2018
dc.identifier.issn2207-1296
dc.identifier.urihttp://hdl.handle.net/10072/383949
dc.description.abstractThis paper investigates whether modulation domain speech en-hancement methods are better than corresponding acoustic do-main methods when used as a preprocessor to automatic speech recognition. It is well known that linguistic information of speech is contained not only in the short-time magnitude spec-trum but also in its temporal evolution. In addition, this study investigates whether popular metrics used in speech enhance-ment (such as PESQ, segmental SNR, STOI) are indicative of ASR performance. ASR experiments on the TIMIT speech cor-pus corrupted by various noises were performed to compare re-cent modulation domain methods with their acoustic domain variants.
dc.publisherASSTA
dc.publisher.urihttp://sst2018.unsw.edu.au
dc.relation.ispartofconferencenameSST 2018
dc.relation.ispartofconferencetitle17th Speech Science and Technology Conference (SST2018)
dc.relation.ispartofdatefrom2018-12-04
dc.relation.ispartofdateto2018-12-07
dc.relation.ispartoflocationSydney, Australia
dc.subject.fieldofresearchSignal Processing
dc.subject.fieldofresearchcode090609
dc.titleA comparative study on acoustic and modulation domain speech enhancement algorithms for improving noise robustness in speech recognition
dc.typeConference output
dc.type.descriptionE1 - Conferences
dc.type.codeE - Conference Publications
dc.description.versionPublished
gro.rights.copyright© 2018 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.authorSo, Stephen
gro.griffith.authorSchwerin, Belinda M.


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