Computational intelligence for speech enhancement using deep neural network

In real time, the speech signal received contains noise produced in the background andreverberations. These disturbances reduce the quality of speech; therefore, it is importantto eliminate the noise and increase the intelligibility and quality of speech signal. Speechenhancement is the primary task in any real-time application that handles speech signals.In the proposed method, the most effective and challenging noise, i.e., babble noise, isremoved, and the clean speech is recovered. The enhancement of the corrupted speechsignal is done by applying a deep neural network-based denoising algorithm in which theideal ratio mask is used to mask the noisy speech and separate the clean speech signal.In the proposed system, the speech signal corrupted by noise is enhanced. Evaluation ofenhanced speech signal by performance metrics such as short time objective intelligibilityand signal to noise ratio of the denoised speech show that the speech intelligibility andspeech quality are improved by the proposed method.

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Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).