2007 IEEE International Conference on Electro/Information Technology 2007
DOI: 10.1109/eit.2007.4374520
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Colored noise reduction using Bark scale spectral subtraction, statistics, and multiple time frames

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Cited by 4 publications
(1 citation statement)
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“…Mihalis Samonas et al [5] used a self-consistent restoration peak preserving algorithm to eliminate the high level additive colored Gaussian noise. David Kozel et al [6] proposed a spectral subtraction algorithm for reducing colored noise from noise-corrupted speech, however with a limitation of the requirement of a favorable signal to noise ratio as with all spectral subtraction algorithms. Jesper Højvang Jensen et al [7] derived the signal amplitude and noise covariance matrix estimator with colored Gaussian noise and extended the existed singlesinusoid algorithm to multiple sinusoids.…”
Section: Introductionmentioning
confidence: 99%
“…Mihalis Samonas et al [5] used a self-consistent restoration peak preserving algorithm to eliminate the high level additive colored Gaussian noise. David Kozel et al [6] proposed a spectral subtraction algorithm for reducing colored noise from noise-corrupted speech, however with a limitation of the requirement of a favorable signal to noise ratio as with all spectral subtraction algorithms. Jesper Højvang Jensen et al [7] derived the signal amplitude and noise covariance matrix estimator with colored Gaussian noise and extended the existed singlesinusoid algorithm to multiple sinusoids.…”
Section: Introductionmentioning
confidence: 99%