Speech enhancement is fundamental for various real time speech applications and it is a challenging task in the case of a single channel because practically only one data channel is available. We have proposed a supervised single channel speech enhancement algorithm in this paper based on a deep neural network (DNN) and less aggressive Wiener filtering as additional DNN layer. During the training stage the network learns and predicts the magnitude spectrums of the clean and noise signals from input noisy speech acoustic features. Relative spectral transform-perceptual linear prediction (RASTA-PLP) is used in the proposed method to extract the acoustic features at the frame level. Autoregressive moving average (ARMA) filter is applied to smooth the temporal curves of extracted features. The trained network predicts the coefficients to construct a ratio mask based on mean square error (MSE) objective cost function. The less aggressive Wiener filter is placed as an additional layer on the top of a DNN to produce an enhanced magnitude spectrum. Finally, the noisy speech phase is used to reconstruct the enhanced speech. The experimental results demonstrate that the proposed DNN framework with less aggressive Wiener filtering outperforms the competing speech enhancement methods in terms of the speech quality and intelligibility.

Slope Stability Analysis is one of the main aspects of Open-pit mine planning because the calculations regarding the stability of slopes are necessary to assess the stability of the open pit slopes together with the financial feasibility of the mining operations. This study was conducted to analyse the effect of groundwater on the shear strength properties of soft rock formations and determine the optimum overall slope angle for an open pit coal mine at Thar Coalfield, Pakistan. Computer modelling and analysis of the slope models were performed using Slide (v. 5.0) and Phase2 (v. 6.0) software. Integrated use of Limit Equilibrium based Probabilistic (LE-P) analysis and Finite Element Method (FEM) based shear strength reduction analysis was performed to determine the safe overall slope angle against circular failure. Several pit slope models were developed at different overall slope angles and pore-water pressure ratio (Ru) coefficients. Each model was initially analysed under dry conditions and then by incorporating the effect of pore-water pressure coefficients of Ru = 0.1, 0.2, and 0.3 (partially saturated); finally, the strata were considered to be fully saturated. It was concluded that at an overall slope angle of 29 degrees, the overall slope will remain stable under dry and saturated conditions for a critical safety factor of 1.3.