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M.Tech M.E PhD Thesis | Digital Signal Processing | Volume 8 Issue 5, May 2019 | Pages: 1640 - 1644 | Burma
Noise Removal in Speech Signal using Modified Berouti Spectral Subtraction for Emotion Recognition
Abstract: In this paper, Berouti Spectral subtraction is used for reducing noise from noisy speech signals. It calculates the spectrum of the noisy speech using the combination of Fast Fourier Transform (FFT) and spectral flux and then the noise spectrum is subtracted from the noisy speech spectrum. The performance of this paper was measured by calculating the Signal to Noise Ratio (SNR). This paper proposes a new parameter for speech enhancement. The idea is to apply the spectral subtraction with spectral flux for estimating the noise more precisely. The new parameter is used for spectral subtraction in unvoiced speech frames and the existing power factor in spectral subtraction method is improved.
Keywords: Speech Enhancement, Spectral Subtraction, Spectral Flux, Emotion Recognition
How to Cite?: May Mon Lynn, Chaw Su, "Noise Removal in Speech Signal using Modified Berouti Spectral Subtraction for Emotion Recognition", Volume 8 Issue 5, May 2019, International Journal of Science and Research (IJSR), Pages: 1640-1644, https://www.ijsr.net/getabstract.php?paperid=ART20197721, DOI: https://dx.doi.org/10.21275/ART20197721