Denoising in the Domain of Spectrotemporal Modulations.
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| Title: | Denoising in the Domain of Spectrotemporal Modulations. |
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| Authors: | Mesgarani, Nima1, Shamma, Shihab1 |
| Source: | EURASIP Journal on Audio Speech & Music Processing. 2007, Vol. 2007, Special section p1-8. 8p. 1 Diagram, 5 Graphs. |
| Subjects: | Spectrograms, Computer sound processing, Wiener's model (Communication), Amplitude modulation detectors, Speech processing systems, Auditory pathways |
| Abstract: | A noise suppression algorithm is proposed based on filtering the spectrotemporal modulations of noisy signals. The modulations are estimated from a multiscale representation of the signal spectrogram generated by a model of sound processing in the auditory system. A significant advantage of this method is its ability to suppress noise that has distinctive modulation patterns, despite being spectrally overlapping with the signal. The performance of the algorithm is evaluated using subjective and objective tests with contaminated speech signals and compared to traditional Wiener filtering method. The results demonstrate the efficacy of the spectrotemporal filtering approach in the conditions examined. [ABSTRACT FROM AUTHOR] |
| Copyright of EURASIP Journal on Audio Speech & Music Processing is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 55253343 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Denoising in the Domain of Spectrotemporal Modulations. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Mesgarani%2C+Nima%22">Mesgarani, Nima</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Shamma%2C+Shihab%22">Shamma, Shihab</searchLink><relatesTo>1</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22EURASIP+Journal+on+Audio+Speech+%26+Music+Processing%22">EURASIP Journal on Audio Speech & Music Processing</searchLink>. 2007, Vol. 2007, Special section p1-8. 8p. 1 Diagram, 5 Graphs. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Spectrograms%22">Spectrograms</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+sound+processing%22">Computer sound processing</searchLink><br /><searchLink fieldCode="DE" term="%22Wiener's+model+%28Communication%29%22">Wiener's model (Communication)</searchLink><br /><searchLink fieldCode="DE" term="%22Amplitude+modulation+detectors%22">Amplitude modulation detectors</searchLink><br /><searchLink fieldCode="DE" term="%22Speech+processing+systems%22">Speech processing systems</searchLink><br /><searchLink fieldCode="DE" term="%22Auditory+pathways%22">Auditory pathways</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: A noise suppression algorithm is proposed based on filtering the spectrotemporal modulations of noisy signals. The modulations are estimated from a multiscale representation of the signal spectrogram generated by a model of sound processing in the auditory system. A significant advantage of this method is its ability to suppress noise that has distinctive modulation patterns, despite being spectrally overlapping with the signal. The performance of the algorithm is evaluated using subjective and objective tests with contaminated speech signals and compared to traditional Wiener filtering method. The results demonstrate the efficacy of the spectrotemporal filtering approach in the conditions examined. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of EURASIP Journal on Audio Speech & Music Processing is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1155/2007/42357 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 8 StartPage: 1 Subjects: – SubjectFull: Spectrograms Type: general – SubjectFull: Computer sound processing Type: general – SubjectFull: Wiener's model (Communication) Type: general – SubjectFull: Amplitude modulation detectors Type: general – SubjectFull: Speech processing systems Type: general – SubjectFull: Auditory pathways Type: general Titles: – TitleFull: Denoising in the Domain of Spectrotemporal Modulations. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Mesgarani, Nima – PersonEntity: Name: NameFull: Shamma, Shihab IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Text: 2007 Type: published Y: 2007 Identifiers: – Type: issn-print Value: 16874714 Numbering: – Type: volume Value: 2007 Titles: – TitleFull: EURASIP Journal on Audio Speech & Music Processing Type: main |
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