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degraded by various additive noise sources verify that significant improvements are possible with the more recent estimators based on super-Gaussian priors. The increase in perceptual evaluation of speech quality (PESQ) over the noisy signals is about 0.5 points for street noise and about 1 point for white noise, nearly independent of input signal-to-noise(More)
We consider estimation of the noise spectral variance from speech signals contaminated by highly nonstationary noise sources. In each time frame, for each frequency bin, the noise variance estimate is updated recursively with the Minimum Mean-Square Error (MMSE) estimate of the current noise power. For the estimation of the noise power, a spectral gain(More)
The combination of radar and radiometer for the retrieval of cloud liquid water profiles is investigated. As the basis for the retrievals we use a profile algorithm similar to the one proposed by Peter and Kämpfer [1], but modified on a few points. The radar is used to provide the algorithm with cloud heights and the shape of liquid water profile.(More)
In 1996 and 1998, measurement campaigns have taken place in the Netherlands and the United Kingdom, respectively. A variety of collocated instruments performed measurements on the clouds. Among the instruments were a microwave radiometer, lidars and radars. Also, particle size measuring probes were operated during flights through the clouds. Estimates of(More)
Recently, dual wavelength radar measurements of smoke and developing cumulus clouds have appeared in the literature which show a puzzling correlation between the measured radar returns. This correlation cannot easily be explained in terms of the conventional scattering mechanisms: coherent (Bragg) scattering from spatial fluctuations in clear-air refractive(More)
—This paper considers estimation of the noise spectral variance from speech signals contaminated by highly nonsta-tionary noise sources. The method can accurately track fast changes in noise power level (up to about 10 dB/s). In each time frame, for each frequency bin, the noise variance estimate is updated recursively with the minimum mean-square error(More)
— A time-domain analysis of the autocorrelation method for autoregressive estimation is given. It is shown that a small bias in a reflection coefficient close to one in absolute value is propagated and prohibits an accurate estimation of further reflection coefficients. Tapered data windows largely reduce this effect, but increase the variance of the models.
—This paper considers suppression of late reverberation and additive noise in single-channel speech recordings. The reverberation introduces long-term correlation in the observed signal. In the first part of this work, we show how this correlation can be used to estimate the late reverberant spectral variance (LRSV) without having to assume a specific model(More)