Abstract
Properties of human audio perception are used to perform spectral and time masking to reduce perceived loudness of noise added to speech signals. A signal is divided into blocks (2), passed through notch filters (4) to remove noise components and then appended to part of the previous block (6). An FFT (8) is then performed on the resulting block and the spectral components are fed to noise estimator (20). Each frequency component is then analyzed to determine whether it is noise. The frequency component's gain function is determined and a spectral valley filler (38) is used to processed the gain function after which the function is used to modify magnitude components of the FFT (12). In inverse FFT (14) then maps the signal back to the time domain to give a frame of noise-reduced signal.
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