Jan S. Erkelens

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This paper considers techniques for single-channel speech enhancement based on the discrete Fourier transform (DFT). Specifically, we derive minimum mean-square error (MMSE) estimators of speech DFT coefficient magnitudes as well as of complex-valued DFT coefficients based on two classes of generalized gamma distributions, under an additive Gaussian noise(More)
Gain functions for spectral noise suppression have been derived in literature for some error criteria and statistical models. These gain functions are only optimal when the statistical model is correct and the speech and noise spectral variances are known. Unfortunately, the speech distributions are unknown and can at best be determined conditionally on the(More)
This paper considers estimation of the noise spectral variance from speech signals contaminated by highly nonstationary 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)
Previously, we showed that offspring from obese rat dams were hyperphagic, with increased adiposity, hyperlipidaemia and glucose intolerance associated with increased orexigenic neuropeptide expression after fasting. Mammalian target of rapamycin (mTOR) can inhibit food intake through a hypothalamic action. As we previously showed that maternal obesity(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)
This letter considers the estimation of speech signals contaminated by additive noise in the discrete Fourier transform (DFT) domain. Existing complex-DFT estimators assume independency of the real and imaginary parts of the speech DFT coefficients, although this is not in line with measurements. In this letter, we derive some general results on these(More)
We consider single-channel blind late-reverberation suppression in noisy and time-varying acoustical environments. Existing estimators for the late reverberant spectral variance (LRSV) are derived assuming the room impulse responses (RIRs) to be time-invariant realizations of a stochastic process. In this paper, we go one step further and analyze(More)
We consider blind late-reverberation suppression in speech signals measured with a single microphone in noisy environments. We exploit that reverberant speech shows correlation over longer time spans than clean speech by predicting the contribution of reverberant energy to the current observed spectrum from the enhanced spectra of previous frames. The(More)