masking_methods.py 文件源码

def IAM(self):
        """
            Computation of Ideal Amplitude Mask. As appears in :
            H. Erdogan, J. R. Hershey, S. Watanabe, and J. Le Roux,
            "Phase-sensitive and recognition-boosted speech separation using deep recurrent neural networks,"
            in ICASSP 2015, Brisbane, April, 2015.
        Args:
            sTarget:   (2D ndarray) Magnitude Spectrogram of the target component
            nResidual: (2D ndarray) Magnitude Spectrogram of the residual component
                                    (In this case the observed mixture should be placed)
        Returns:
            mask:      (2D ndarray) Array that contains time frequency gain values

        """
        print('Ideal Amplitude Mask')
        self._mask = np.divide(self._sTarget, (self._eps + self._nResidual))