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Article: A Hilbert-fine-structure-derived physical metric for predicting the intelligibility of noise-distorted and noise-suppressed speech

TitleA Hilbert-fine-structure-derived physical metric for predicting the intelligibility of noise-distorted and noise-suppressed speech
Authors
KeywordsSpeech intelligibility
Hilbert fine-structure signal
Speech transmission index
Issue Date2013
PublisherElsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/specom
Citation
Speech Communication, 2013, v. 55 n. 10, p. 1011-1020 How to Cite?
AbstractDespite the established importance of temporal fine-structure (TFS) on speech perception in noise, existing speech transmission metrics use primarily envelope information to model speech intelligibility variance. This study proposes a new physical metric for predicting speech intelligibility using information obtained from the Hilbert-derived TFS waveform. It is found that by making explicit use of coherence information contained in the complex spectra of the Hilbert-derived TFS waveforms of the clean and corrupted speech signals, and assessing the extent to which the coherence in the Hilbert fine structure is affected following the linear or non-linear processing (e.g., noise distortion, speech enhancement, etc.) of the stimulus, the predictive power of the intelligibility measure can be significantly improved for noise-distorted and noise-suppressed speech signals. When evaluated with speech recognition scores obtained with normal-hearing listeners, including a total of sixty-four noise-suppressed conditions with nonlinear distortions and eight noisy conditions without subsequent noise reduction, the proposed TFS-based measure was found to predict speech intelligibility better than most envelope- and coherence-based measures. High correlation was maintained for all types of maskers tested, with a maximum correlation of r = 0.95 achieved in car and street noise conditions.
Persistent Identifierhttp://hdl.handle.net/10722/184718
ISSN
2019 Impact Factor: 1.417
2015 SCImago Journal Rankings: 0.685
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorChen, FF-
dc.contributor.authorWong, LLN-
dc.contributor.authorHu, Y-
dc.date.accessioned2013-07-15T10:05:38Z-
dc.date.available2013-07-15T10:05:38Z-
dc.date.issued2013-
dc.identifier.citationSpeech Communication, 2013, v. 55 n. 10, p. 1011-1020-
dc.identifier.issn0167-6393-
dc.identifier.urihttp://hdl.handle.net/10722/184718-
dc.description.abstractDespite the established importance of temporal fine-structure (TFS) on speech perception in noise, existing speech transmission metrics use primarily envelope information to model speech intelligibility variance. This study proposes a new physical metric for predicting speech intelligibility using information obtained from the Hilbert-derived TFS waveform. It is found that by making explicit use of coherence information contained in the complex spectra of the Hilbert-derived TFS waveforms of the clean and corrupted speech signals, and assessing the extent to which the coherence in the Hilbert fine structure is affected following the linear or non-linear processing (e.g., noise distortion, speech enhancement, etc.) of the stimulus, the predictive power of the intelligibility measure can be significantly improved for noise-distorted and noise-suppressed speech signals. When evaluated with speech recognition scores obtained with normal-hearing listeners, including a total of sixty-four noise-suppressed conditions with nonlinear distortions and eight noisy conditions without subsequent noise reduction, the proposed TFS-based measure was found to predict speech intelligibility better than most envelope- and coherence-based measures. High correlation was maintained for all types of maskers tested, with a maximum correlation of r = 0.95 achieved in car and street noise conditions.-
dc.languageeng-
dc.publisherElsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/specom-
dc.relation.ispartofSpeech Communication-
dc.subjectSpeech intelligibility-
dc.subjectHilbert fine-structure signal-
dc.subjectSpeech transmission index-
dc.titleA Hilbert-fine-structure-derived physical metric for predicting the intelligibility of noise-distorted and noise-suppressed speech-
dc.typeArticle-
dc.identifier.emailChen, FF: feichen1@hku.hk-
dc.identifier.emailWong, LLN: llnwong@hku.hk-
dc.identifier.authorityChen, FF=rp01593-
dc.identifier.authorityWong, LLN=rp00975-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.specom.2013.06.016-
dc.identifier.scopuseid_2-s2.0-84881406707-
dc.identifier.hkuros216595-
dc.identifier.hkuros219367-
dc.identifier.volume55-
dc.identifier.issue10-
dc.identifier.spage1011-
dc.identifier.epage1020-
dc.identifier.isiWOS:000324227500007-
dc.publisher.placeNetherlands-

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