masking_methods.py 文件源码

def alphaHarmonizableProcess(self):
        """
            Computation of Wiener like mask using fractional power spectrograms. As appears in :
            A. Liutkus, R. Badeau, "Generalized Wiener filtering with fractional power spectrograms",
            40th International Conference on Acoustics, Speech and Signal Processing (ICASSP),
            Apr 2015, Brisbane, Australia.
        Args:
            sTarget:   (2D ndarray) Magnitude Spectrogram of the target component
            nResidual: (2D ndarray) Magnitude Spectrogram of the residual component or a list 
                                    of 2D ndarrays which will be added together
        Returns:
            mask:      (2D ndarray) Array that contains time frequency gain values

        """
        print('Harmonizable Process with alpha:', str(self._alpha))
        localsTarget = self._sTarget ** self._alpha
        numElements = len(self._nResidual)
        if numElements > 1:
            localnResidual = self._nResidual[0] ** self._alpha + localsTarget
            for indx in range(1, numElements):
                localnResidual += self._nResidual[indx] ** self._alpha
        else :
            localnResidual = self._nResidual[0] ** self._alpha + localsTarget

        self._mask = np.divide((localsTarget + self._eps), (self._eps + localnResidual))