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dc.contributor.authorSchwerin, Belinda
dc.contributor.authorPaliwal, Kuldip
dc.date.accessioned2017-05-03T11:36:49Z
dc.date.available2017-05-03T11:36:49Z
dc.date.issued2014
dc.identifier.issn0167-6393
dc.identifier.doi10.1016/j.specom.2014.05.003
dc.identifier.urihttp://hdl.handle.net/10072/64207
dc.description.abstractThe speech transmission index (STI) is a well known measure of intelligibility, most suited to the evaluation of speech intelligibility in rooms, with stimuli subjected to additive noise and reverberance. However, STI and its many variations do not effectively represent the intelligibility of stimuli containing non-linear distortions such as those resulting from processing by enhancement algorithms. In this paper, we revisit the STI approach and propose a variation which processes the modulation envelope in short-time segments, requiring only an assumption of quasi-stationarity (rather than the stationarity assumption of STI) of the modulation signal. Results presented in this work show that the proposed approach improves the measures correlation to subjective intelligibility scores compared to traditional STI for a range of noise types and subjected to different enhancement approaches. The approach is also shown to have higher correlation than other coherence, correlation and distance measures tested, but is unsuited to the evaluation of stimuli heavily distorted with (for example) masking based processing, where an alternative approach such as STOI is recommended.
dc.description.peerreviewedYes
dc.description.publicationstatusYes
dc.languageEnglish
dc.language.isoeng
dc.publisherElsevier
dc.publisher.placeNetherlands
dc.relation.ispartofstudentpublicationN
dc.relation.ispartofpagefrom9
dc.relation.ispartofpageto19
dc.relation.ispartofjournalSpeech Communication
dc.relation.ispartofvolume65
dc.rights.retentionY
dc.subject.fieldofresearchSignal processing
dc.subject.fieldofresearchCognitive and computational psychology
dc.subject.fieldofresearchLinguistics
dc.subject.fieldofresearchCommunications engineering
dc.subject.fieldofresearchArtificial intelligence
dc.subject.fieldofresearchcode400607
dc.subject.fieldofresearchcode5204
dc.subject.fieldofresearchcode4704
dc.subject.fieldofresearchcode4006
dc.subject.fieldofresearchcode4602
dc.titleAn improved speech transmission index for intelligibility prediction
dc.typeJournal article
dc.type.descriptionC1 - Articles
dc.type.codeC - Journal Articles
gro.facultyGriffith Sciences, Griffith School of Engineering
gro.hasfulltextNo Full Text
gro.griffith.authorSchwerin, Belinda M.
gro.griffith.authorPaliwal, Kuldip K.


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