Gaussian Mixture Models (GMMs) of power spectral densities of speech and noise are used with explicit Bayesian estimations in Wiener filtering of noisy speech. No assumption is made on the nature or stationarity of the noise. No voice activity detection (VAD) or any other means is employed to estimate the input SNR. The GMM mean vectors are used to form sets of over-determined system of equatio...

While i-vectors with probabilistic linear discriminant analysis (PLDA) can achieve state-of-the-art performance in speaker verification, the mismatch caused by acoustic noise remains a key factor affecting system performance. In this paper, a fusion system that combines a multi-condition SNR-independent PLDA model and a mixture of SNR-dependent PLDA models is proposed to make speaker verificati...

This paper proposes a signal-to-noise-ratio (SNR) aware convolutional neural network (CNN) model for speech enhancement (SE). Because the CNN model can deal with local temporal-spectral structures of speech signals, it can effectively disentangle the speech and noise signals given the noisy speech signals. In order to enhance the generalization capability and accuracy, we propose two SNR-aware ...

In this paper, a novel two-step non-data-aided (NDA) signal to noise ratio (SNR) estimator is proposed to improve its accuracy in the low SNR region of orthogonal frequency division multiplexing (OFDM) signals. The two-step estimator consists of a coarse estimation followed by a refinement step. In the first step, three linear independent coarse estimations of the signal and noise power are obt...

Recently, intelligent reflecting surfaces (IRSs) and unmanned aerial vehicles (UAVs) have been integrated into wireless communication systems to enhance the performance of air–ground transmission. To balance performance, cost, power consumption well, a hybrid IRS UAV-assisted directional modulation (DM) network is investigated in this paper which consisted passive active elements. We aimed maxi...

The most important parameter that affects the ability to hear and understand speech in the presence of background noise is the signal-to-noise ratio (SNR). Despite decades of research in speech intelligibility, it is not currently known how much improvement in SNR is needed to provide a meaningful benefit to someone. We propose that the underlying psychophysical basis to a meaningful benefit sh...

Pseudomonas aeruginosa is able to use nitrate for both assimilation and anaerobic respiration. One set of genes, designated snr (for "shared nitrate reduction"), have been recently cloned and partially characterized. In this study, we demonstrate that the snr-1 gene encodes a predicted 52.5-kDa protein that is 82% similar to a unique cytochrome c of Desulfomonile tiedjei DCB-1. Importantly, the...

This paper studies the output-input signal-to-noise ratio (SNR) gain of an uncoupled parallel array of static, yet arbitrary, nonlinear elements for transmitting a weak periodic signal in additive white noise. In the small-signal limit, an explicit expression for the SNR gain is derived. It serves to prove that the SNR gain is always a monotonically increasing function of the array size for any...

In wireless communications, power allocation plays a paramount role in sustainable network lifetime prolongation with quality-of-service and network interference reduction. This paper investigates a distributed power allocation problem in wireless parallel amplify-and-forward (AF) relay transmissions. Particularly, the objective is set to minimize the total transmit power while guaranteeing the...