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A blind source separation with fractional calculus for noise reduction in speech enhancement
Pramodini Shrihari Talware, , SP Mahajan
Published in Institute of Electrical and Electronics Engineers Inc.
Volume: 2017-January
Pages: 1 - 6
A Blind Source Separation with Fractional Calculus for Noise Reduction in Speech enhancement is proposed in this paper. Different strategies are available for reduction of noise. Fractional calculus has been recently applied in various zones like engineering, science, bio-engineering and finance. It has numerous applications, for example, use in differentiation, integral equations, signal processing, fluid mechanics, and electrochemistry. In this work speech processing signal application where Discrete Fractional Fourier Transform (DFRFT) is used which is an essential process for signal processing. DFRFT has DFT hermite Eigenvectors and retains the eigenvalue eigen operate relation as a fractional fourier transform that reconstruct the signal. For the purpose of noise reduction, Blind Source Separation has been utilizing which does not have prior knowledge of original signal. DFRFT algorithm and SNR are used to prove that the improvement of the processed enhanced signal as compared to the noisy signal. © 2017 IEEE.