In this paper we investigate the enhancement of speech by applying MMSE short-time spectral magnitude estimation in the modulation domain. For this purpose, the traditional analysis-modification-synthesis framework is extended to include modulation domain processing. We compensate the noisy modulation spectrum for additive noise distortion by applying the MMSE short-time spectral magnitude esti...

We present an O(M logM) method for estimating M -dimensional structured channels that uses techniques from the field of machine learning. Our channel model is typical in communications: the channel vector is normal distributed given an unknown covariance matrix, which depends on random hyperparameters such as the angles of the propagation paths. If the channel model exhibits certain Toeplitz an...

In this paper, the minimum mean-square error (MMSE) ˇ-order estimator for multichannel speech enhancement is proposed. The estimator is an extension of the single-channel MMSE ˇ-order and multichannel MMSE short-time spectral amplitude estimators using Rayleigh and Gaussian distributions for the statistical models under the assumption of a diffuse noise field where the noise is estimated indepe...

Abstract—This paper considers detection techniques for unresolved Ricean/Rayleigh fading multipath channels. It is wellknown that the optimal receiver has an estimator-correlator form, with a Minimum Mean-Square Error (MMSE) estimate. With known multipath delays and unknown specular phases, the Ricean non-coherent multipath channel is a case where the received noiseless signal process is non-Ga...

This paper develops and compares the MAP and MMSE estimators for spherically-contoured multivariate Laplace random vectors in additive white Gaussian noise. The MMSE estimator is expressed in closed-form using the generalized incomplete gamma function. We also find a computationally efficient yet accurate approximation for the MMSE estimator. In addition, this paper develops an expression for t...

The choice of channel estimation is of fundamental importance in OFDM receiver designs, which further involves a trade-off between complexity and estimation accuracy. In pilot-symbol-aided OFDM system, the Least Square (LS) estimator suffers from inherent additive Gaussian noise and Inter Carrier Interference (ICI), although the estimator exhibits lower complexity and requires implicit knowledg...

In this paper we present an MMSE (minimum mean square error) speech feature enhancement algorithm, capitalizing on a new probabilistic, nonlinear environment model that effectively incorporates the phase relationship between the clean speech and the corrupting noise in acoustic distortion. The MMSE estimator based on this phase-sensitive model is derived and it achieves high efficiency by explo...

In this paper, we investigate the use of the minimum mean square error (MMSE) spectral energy estimator for use in environmentrobust automatic speech recognition (ASR). In the past, it has been common to use the MMSE log-spectral amplitude estimator for this task. However, this estimator was originally derived under subjective human listening criteria. Therefore its complex suppression rule may...

Orthogonal frequency division multiplexing (OFDM) is a keytechnique for wireless communication because of its robustness for narrow band interference, frequency selective fading and spectral efficiency. Channel estimation and equalization in OFDM is necessary in order to nullify the effect of impairments induced by the frequency selective fading channel. A frequency domain comb typepilot assist...