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In this research work, we propose the model based on the Genetic Algorithm (GA) and Deep Neural Network (DNN) to enhance the quality and intelligibility of the noisy speech. In this proposed model, the Voiced Speech (VS) T-F mask is computed using correlogram, frame energy and cross-channel correlogram and Unvoiced Speech (UVS) T-F mask is computed using speech onset/offset. The T-F mask obtained using speech onset and offset represents both voiced and unvoiced segment of the noisy speech signal. The UVS T-F mask is obtained by subtracting the VS from the T-F mask obtained earlier using speech onset/offset. Next, the GA is used to find the optimum weight to combine the T-F mask of VS and UVS to improve speech quality and intelligibility. The weight obtained using GA may not be an optimum one for all sets of speech and noise. This research work focuses on this issue and proposes a DNN …