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The main aim of the Speech Enhancement algorithms is to improve the Quality of speech. The Quality of speech is expressed in two parameters. One is clarity, and another is intelligibility. In this paper, we proposed a method to improve the quality of speech based on computationally efficient AR modeled Iterative Kalman Filter with time and frequency mask. This approach is based on reconstruction of noisy speech signals using Auto Regressive modeled Kalman filter and further to reduce artifact noise time and frequency mask is applied to the Kalman filter output. The results of the proposed method are found to be better compared to spectral subtraction, wiener filter and Kalman filter methods.

Speech Enhancement Using Iterative Kalman Filter with Time and Frequency Mask in Different Noisy Environment