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Generally, the recorded speech signal is corrupted by both room reverberation and background noise leading to a reduced speech quality and intelligibility. In order to deal with the distortions caused by the joint effect of noise and reverberation, we propose a context-aware-based deep neural network (DNN) approach for simultaneous speech denoising and dereverberation. The proposed system consists of two stages such as denoising stage and the dereverberation stage. In the denoising stage, the additive noise is suppressed by estimating a phase-sensitive mask using DNN. Then, the noise-free reverberant speech is processed through the dereverberation stage. In the dereverberation stage, a reverberation-time-aware DNN-based model is used to perform dereverberation by adopting two reverberation time-dependent parameters such as frameshift size and acoustic context size to get the benefits of the …