Speech enhancement using an MMSE short time DCT coefficients estimator with supergaussian speech modeling
Abstract In this paper, two speech enhancement systems with supergaussian speech modeling are presented. The clean speech components are estimated by Minimum-Mean-Square-Error (MMSE) estimator under the assumption that the DCT coefficients of clean speech are modeled by a Laplacian or a Gamma distri...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Zou, Xia [verfasserIn] |
|---|
| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2007 |
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| Anmerkung: |
© Science Press 2007 |
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| Übergeordnetes Werk: |
Enthalten in: Journal of electronics (China) - Beijing : Science Pr., 1984, 24(2007), 3 vom: 01. Mai, Seite 332-337 |
|---|---|
| Übergeordnetes Werk: |
volume:24 ; year:2007 ; number:3 ; day:01 ; month:05 ; pages:332-337 |
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| DOI / URN: |
10.1007/s11767-005-0174-y |
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| 520 | |a Abstract In this paper, two speech enhancement systems with supergaussian speech modeling are presented. The clean speech components are estimated by Minimum-Mean-Square-Error (MMSE) estimator under the assumption that the DCT coefficients of clean speech are modeled by a Laplacian or a Gamma distribution and the DCT coefficients of the noise are Gaussian distributed. Then, MMSE estimators under speech presence uncertainty are derived. Furthermore, the proper estimators of the speech statistical parameters are proposed. The speech Laplacian factor is estimated by a new decision-directed method. The simulation results show that the proposed algorithm yields less residual noise and better speech quality than the Gaussian based speech enhancement algorithms proposed in recent years. | ||
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10.1007/s11767-005-0174-y doi (DE-627)SPR022301623 (SPR)s11767-005-0174-y-e DE-627 ger DE-627 rakwb eng Zou, Xia verfasserin aut Speech enhancement using an MMSE short time DCT coefficients estimator with supergaussian speech modeling 2007 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Science Press 2007 Abstract In this paper, two speech enhancement systems with supergaussian speech modeling are presented. The clean speech components are estimated by Minimum-Mean-Square-Error (MMSE) estimator under the assumption that the DCT coefficients of clean speech are modeled by a Laplacian or a Gamma distribution and the DCT coefficients of the noise are Gaussian distributed. Then, MMSE estimators under speech presence uncertainty are derived. Furthermore, the proper estimators of the speech statistical parameters are proposed. The speech Laplacian factor is estimated by a new decision-directed method. The simulation results show that the proposed algorithm yields less residual noise and better speech quality than the Gaussian based speech enhancement algorithms proposed in recent years. Zhang, Xiongwei aut Enthalten in Journal of electronics (China) Beijing : Science Pr., 1984 24(2007), 3 vom: 01. Mai, Seite 332-337 (DE-627)537443169 (DE-600)2376287-1 1993-0615 nnns volume:24 year:2007 number:3 day:01 month:05 pages:332-337 https://dx.doi.org/10.1007/s11767-005-0174-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_31 GBV_ILN_40 GBV_ILN_60 GBV_ILN_63 GBV_ILN_65 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_110 GBV_ILN_120 GBV_ILN_150 GBV_ILN_161 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_374 GBV_ILN_702 GBV_ILN_2190 GBV_ILN_2700 GBV_ILN_4313 GBV_ILN_4328 AR 24 2007 3 01 05 332-337 |
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10.1007/s11767-005-0174-y doi (DE-627)SPR022301623 (SPR)s11767-005-0174-y-e DE-627 ger DE-627 rakwb eng Zou, Xia verfasserin aut Speech enhancement using an MMSE short time DCT coefficients estimator with supergaussian speech modeling 2007 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Science Press 2007 Abstract In this paper, two speech enhancement systems with supergaussian speech modeling are presented. The clean speech components are estimated by Minimum-Mean-Square-Error (MMSE) estimator under the assumption that the DCT coefficients of clean speech are modeled by a Laplacian or a Gamma distribution and the DCT coefficients of the noise are Gaussian distributed. Then, MMSE estimators under speech presence uncertainty are derived. Furthermore, the proper estimators of the speech statistical parameters are proposed. The speech Laplacian factor is estimated by a new decision-directed method. The simulation results show that the proposed algorithm yields less residual noise and better speech quality than the Gaussian based speech enhancement algorithms proposed in recent years. Zhang, Xiongwei aut Enthalten in Journal of electronics (China) Beijing : Science Pr., 1984 24(2007), 3 vom: 01. Mai, Seite 332-337 (DE-627)537443169 (DE-600)2376287-1 1993-0615 nnns volume:24 year:2007 number:3 day:01 month:05 pages:332-337 https://dx.doi.org/10.1007/s11767-005-0174-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_31 GBV_ILN_40 GBV_ILN_60 GBV_ILN_63 GBV_ILN_65 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_110 GBV_ILN_120 GBV_ILN_150 GBV_ILN_161 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_374 GBV_ILN_702 GBV_ILN_2190 GBV_ILN_2700 GBV_ILN_4313 GBV_ILN_4328 AR 24 2007 3 01 05 332-337 |
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10.1007/s11767-005-0174-y doi (DE-627)SPR022301623 (SPR)s11767-005-0174-y-e DE-627 ger DE-627 rakwb eng Zou, Xia verfasserin aut Speech enhancement using an MMSE short time DCT coefficients estimator with supergaussian speech modeling 2007 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Science Press 2007 Abstract In this paper, two speech enhancement systems with supergaussian speech modeling are presented. The clean speech components are estimated by Minimum-Mean-Square-Error (MMSE) estimator under the assumption that the DCT coefficients of clean speech are modeled by a Laplacian or a Gamma distribution and the DCT coefficients of the noise are Gaussian distributed. Then, MMSE estimators under speech presence uncertainty are derived. Furthermore, the proper estimators of the speech statistical parameters are proposed. The speech Laplacian factor is estimated by a new decision-directed method. The simulation results show that the proposed algorithm yields less residual noise and better speech quality than the Gaussian based speech enhancement algorithms proposed in recent years. Zhang, Xiongwei aut Enthalten in Journal of electronics (China) Beijing : Science Pr., 1984 24(2007), 3 vom: 01. Mai, Seite 332-337 (DE-627)537443169 (DE-600)2376287-1 1993-0615 nnns volume:24 year:2007 number:3 day:01 month:05 pages:332-337 https://dx.doi.org/10.1007/s11767-005-0174-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_31 GBV_ILN_40 GBV_ILN_60 GBV_ILN_63 GBV_ILN_65 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_110 GBV_ILN_120 GBV_ILN_150 GBV_ILN_161 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_374 GBV_ILN_702 GBV_ILN_2190 GBV_ILN_2700 GBV_ILN_4313 GBV_ILN_4328 AR 24 2007 3 01 05 332-337 |
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10.1007/s11767-005-0174-y doi (DE-627)SPR022301623 (SPR)s11767-005-0174-y-e DE-627 ger DE-627 rakwb eng Zou, Xia verfasserin aut Speech enhancement using an MMSE short time DCT coefficients estimator with supergaussian speech modeling 2007 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Science Press 2007 Abstract In this paper, two speech enhancement systems with supergaussian speech modeling are presented. The clean speech components are estimated by Minimum-Mean-Square-Error (MMSE) estimator under the assumption that the DCT coefficients of clean speech are modeled by a Laplacian or a Gamma distribution and the DCT coefficients of the noise are Gaussian distributed. Then, MMSE estimators under speech presence uncertainty are derived. Furthermore, the proper estimators of the speech statistical parameters are proposed. The speech Laplacian factor is estimated by a new decision-directed method. The simulation results show that the proposed algorithm yields less residual noise and better speech quality than the Gaussian based speech enhancement algorithms proposed in recent years. Zhang, Xiongwei aut Enthalten in Journal of electronics (China) Beijing : Science Pr., 1984 24(2007), 3 vom: 01. Mai, Seite 332-337 (DE-627)537443169 (DE-600)2376287-1 1993-0615 nnns volume:24 year:2007 number:3 day:01 month:05 pages:332-337 https://dx.doi.org/10.1007/s11767-005-0174-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_31 GBV_ILN_40 GBV_ILN_60 GBV_ILN_63 GBV_ILN_65 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_110 GBV_ILN_120 GBV_ILN_150 GBV_ILN_161 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_374 GBV_ILN_702 GBV_ILN_2190 GBV_ILN_2700 GBV_ILN_4313 GBV_ILN_4328 AR 24 2007 3 01 05 332-337 |
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10.1007/s11767-005-0174-y doi (DE-627)SPR022301623 (SPR)s11767-005-0174-y-e DE-627 ger DE-627 rakwb eng Zou, Xia verfasserin aut Speech enhancement using an MMSE short time DCT coefficients estimator with supergaussian speech modeling 2007 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Science Press 2007 Abstract In this paper, two speech enhancement systems with supergaussian speech modeling are presented. The clean speech components are estimated by Minimum-Mean-Square-Error (MMSE) estimator under the assumption that the DCT coefficients of clean speech are modeled by a Laplacian or a Gamma distribution and the DCT coefficients of the noise are Gaussian distributed. Then, MMSE estimators under speech presence uncertainty are derived. Furthermore, the proper estimators of the speech statistical parameters are proposed. The speech Laplacian factor is estimated by a new decision-directed method. The simulation results show that the proposed algorithm yields less residual noise and better speech quality than the Gaussian based speech enhancement algorithms proposed in recent years. Zhang, Xiongwei aut Enthalten in Journal of electronics (China) Beijing : Science Pr., 1984 24(2007), 3 vom: 01. Mai, Seite 332-337 (DE-627)537443169 (DE-600)2376287-1 1993-0615 nnns volume:24 year:2007 number:3 day:01 month:05 pages:332-337 https://dx.doi.org/10.1007/s11767-005-0174-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_31 GBV_ILN_40 GBV_ILN_60 GBV_ILN_63 GBV_ILN_65 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_110 GBV_ILN_120 GBV_ILN_150 GBV_ILN_161 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_374 GBV_ILN_702 GBV_ILN_2190 GBV_ILN_2700 GBV_ILN_4313 GBV_ILN_4328 AR 24 2007 3 01 05 332-337 |
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Speech enhancement using an MMSE short time DCT coefficients estimator with supergaussian speech modeling |
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Abstract In this paper, two speech enhancement systems with supergaussian speech modeling are presented. The clean speech components are estimated by Minimum-Mean-Square-Error (MMSE) estimator under the assumption that the DCT coefficients of clean speech are modeled by a Laplacian or a Gamma distribution and the DCT coefficients of the noise are Gaussian distributed. Then, MMSE estimators under speech presence uncertainty are derived. Furthermore, the proper estimators of the speech statistical parameters are proposed. The speech Laplacian factor is estimated by a new decision-directed method. The simulation results show that the proposed algorithm yields less residual noise and better speech quality than the Gaussian based speech enhancement algorithms proposed in recent years. © Science Press 2007 |
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Abstract In this paper, two speech enhancement systems with supergaussian speech modeling are presented. The clean speech components are estimated by Minimum-Mean-Square-Error (MMSE) estimator under the assumption that the DCT coefficients of clean speech are modeled by a Laplacian or a Gamma distribution and the DCT coefficients of the noise are Gaussian distributed. Then, MMSE estimators under speech presence uncertainty are derived. Furthermore, the proper estimators of the speech statistical parameters are proposed. The speech Laplacian factor is estimated by a new decision-directed method. The simulation results show that the proposed algorithm yields less residual noise and better speech quality than the Gaussian based speech enhancement algorithms proposed in recent years. © Science Press 2007 |
| abstract_unstemmed |
Abstract In this paper, two speech enhancement systems with supergaussian speech modeling are presented. The clean speech components are estimated by Minimum-Mean-Square-Error (MMSE) estimator under the assumption that the DCT coefficients of clean speech are modeled by a Laplacian or a Gamma distribution and the DCT coefficients of the noise are Gaussian distributed. Then, MMSE estimators under speech presence uncertainty are derived. Furthermore, the proper estimators of the speech statistical parameters are proposed. The speech Laplacian factor is estimated by a new decision-directed method. The simulation results show that the proposed algorithm yields less residual noise and better speech quality than the Gaussian based speech enhancement algorithms proposed in recent years. © Science Press 2007 |
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Speech enhancement using an MMSE short time DCT coefficients estimator with supergaussian speech modeling |
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