Quadratic approach for single-channel noise reduction
Abstract In this paper, we introduce a quadratic approach for single-channel noise reduction. The desired signal magnitude is estimated by applying a linear filter to a modified version of the observations’ vector. The modified version is constructed from a Kronecker product of the observations’ vec...
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| Format: | Article |
| Language: | English |
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SpringerOpen
2020-04-01
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| Series: | EURASIP Journal on Audio, Speech, and Music Processing |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s13636-020-00174-4 |
| _version_ | 1828786640789700608 |
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| author | Gal Itzhak Jacob Benesty Israel Cohen |
| author_facet | Gal Itzhak Jacob Benesty Israel Cohen |
| author_sort | Gal Itzhak |
| collection | DOAJ |
| description | Abstract In this paper, we introduce a quadratic approach for single-channel noise reduction. The desired signal magnitude is estimated by applying a linear filter to a modified version of the observations’ vector. The modified version is constructed from a Kronecker product of the observations’ vector with its complex conjugate. The estimated signal magnitude is multiplied by a complex exponential whose phase is obtained using a conventional linear filtering approach. We focus on the linear and quadratic maximum signal-to-noise ratio (SNR) filters and demonstrate that the quadratic filter is superior in terms of subband SNR gains. In addition, in the context of speech enhancement, we show that the quadratic filter is ideally preferable in terms of perceptual evaluation of speech quality (PESQ) and short-time objective intelligibility (STOI) scores. The advantages, compared to the conventional linear filtering approach, are particularly significant for low input SNRs, at the expanse of a higher computational complexity. The results are verified in practical scenarios with nonstationary noise and in comparison to well-known speech enhancement methods. We demonstrate that the quadratic maximum SNR filter may be superior, depending on the nonstationary noise type. |
| first_indexed | 2024-12-12T00:15:08Z |
| format | Article |
| id | doaj.art-b219a4bbcb4744d382c5f7ab64cd4b84 |
| institution | Directory Open Access Journal |
| issn | 1687-4722 |
| language | English |
| last_indexed | 2024-12-12T00:15:08Z |
| publishDate | 2020-04-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | EURASIP Journal on Audio, Speech, and Music Processing |
| spelling | doaj.art-b219a4bbcb4744d382c5f7ab64cd4b842022-12-22T00:44:52ZengSpringerOpenEURASIP Journal on Audio, Speech, and Music Processing1687-47222020-04-012020111410.1186/s13636-020-00174-4Quadratic approach for single-channel noise reductionGal Itzhak0Jacob Benesty1Israel Cohen2Technion, Israel Institute of TechnologyINRS-EMT, University of QuebecTechnion, Israel Institute of TechnologyAbstract In this paper, we introduce a quadratic approach for single-channel noise reduction. The desired signal magnitude is estimated by applying a linear filter to a modified version of the observations’ vector. The modified version is constructed from a Kronecker product of the observations’ vector with its complex conjugate. The estimated signal magnitude is multiplied by a complex exponential whose phase is obtained using a conventional linear filtering approach. We focus on the linear and quadratic maximum signal-to-noise ratio (SNR) filters and demonstrate that the quadratic filter is superior in terms of subband SNR gains. In addition, in the context of speech enhancement, we show that the quadratic filter is ideally preferable in terms of perceptual evaluation of speech quality (PESQ) and short-time objective intelligibility (STOI) scores. The advantages, compared to the conventional linear filtering approach, are particularly significant for low input SNRs, at the expanse of a higher computational complexity. The results are verified in practical scenarios with nonstationary noise and in comparison to well-known speech enhancement methods. We demonstrate that the quadratic maximum SNR filter may be superior, depending on the nonstationary noise type.http://link.springer.com/article/10.1186/s13636-020-00174-4Quadratic filteringMaximum SNR filterFrequency-domain filteringOptimal filtersNonlinear processingKronecker product |
| spellingShingle | Gal Itzhak Jacob Benesty Israel Cohen Quadratic approach for single-channel noise reduction EURASIP Journal on Audio, Speech, and Music Processing Quadratic filtering Maximum SNR filter Frequency-domain filtering Optimal filters Nonlinear processing Kronecker product |
| title | Quadratic approach for single-channel noise reduction |
| title_full | Quadratic approach for single-channel noise reduction |
| title_fullStr | Quadratic approach for single-channel noise reduction |
| title_full_unstemmed | Quadratic approach for single-channel noise reduction |
| title_short | Quadratic approach for single-channel noise reduction |
| title_sort | quadratic approach for single channel noise reduction |
| topic | Quadratic filtering Maximum SNR filter Frequency-domain filtering Optimal filters Nonlinear processing Kronecker product |
| url | http://link.springer.com/article/10.1186/s13636-020-00174-4 |
| work_keys_str_mv | AT galitzhak quadraticapproachforsinglechannelnoisereduction AT jacobbenesty quadraticapproachforsinglechannelnoisereduction AT israelcohen quadraticapproachforsinglechannelnoisereduction |