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- Publisher Website: 10.1016/j.specom.2013.06.016
- Scopus: eid_2-s2.0-84881406707
- WOS: WOS:000324227500007
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Article: A Hilbert-fine-structure-derived physical metric for predicting the intelligibility of noise-distorted and noise-suppressed speech
Title | A Hilbert-fine-structure-derived physical metric for predicting the intelligibility of noise-distorted and noise-suppressed speech |
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Authors | |
Keywords | Speech intelligibility Hilbert fine-structure signal Speech transmission index |
Issue Date | 2013 |
Publisher | Elsevier 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? |
Abstract | Despite 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 Identifier | http://hdl.handle.net/10722/184718 |
ISSN | 2023 Impact Factor: 2.4 2023 SCImago Journal Rankings: 0.769 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Chen, FF | - |
dc.contributor.author | Wong, LLN | - |
dc.contributor.author | Hu, Y | - |
dc.date.accessioned | 2013-07-15T10:05:38Z | - |
dc.date.available | 2013-07-15T10:05:38Z | - |
dc.date.issued | 2013 | - |
dc.identifier.citation | Speech Communication, 2013, v. 55 n. 10, p. 1011-1020 | - |
dc.identifier.issn | 0167-6393 | - |
dc.identifier.uri | http://hdl.handle.net/10722/184718 | - |
dc.description.abstract | Despite 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.language | eng | - |
dc.publisher | Elsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/specom | - |
dc.relation.ispartof | Speech Communication | - |
dc.subject | Speech intelligibility | - |
dc.subject | Hilbert fine-structure signal | - |
dc.subject | Speech transmission index | - |
dc.title | A Hilbert-fine-structure-derived physical metric for predicting the intelligibility of noise-distorted and noise-suppressed speech | - |
dc.type | Article | - |
dc.identifier.email | Chen, FF: feichen1@hku.hk | - |
dc.identifier.email | Wong, LLN: llnwong@hku.hk | - |
dc.identifier.authority | Chen, FF=rp01593 | - |
dc.identifier.authority | Wong, LLN=rp00975 | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1016/j.specom.2013.06.016 | - |
dc.identifier.scopus | eid_2-s2.0-84881406707 | - |
dc.identifier.hkuros | 216595 | - |
dc.identifier.hkuros | 219367 | - |
dc.identifier.volume | 55 | - |
dc.identifier.issue | 10 | - |
dc.identifier.spage | 1011 | - |
dc.identifier.epage | 1020 | - |
dc.identifier.isi | WOS:000324227500007 | - |
dc.publisher.place | Netherlands | - |
dc.identifier.issnl | 0167-6393 | - |