masking_methods.py 文件源码

def ExpM(self):
        """
            Approximate a signal via element-wise exponentiation. As appears in :
            S.I. Mimilakis, K. Drossos, T. Virtanen, and G. Schuller,
            "Deep Neural Networks for Dynamic Range Compression in Mastering Applications,"
            in proc. of the 140th Audio Engineering Society Convention, Paris, 2016.
        Args:
            sTarget:   (2D ndarray) Magnitude Spectrogram of the target component
            nResidual: (2D ndarray) Magnitude Spectrogram of the residual component
        Returns:
            mask:      (2D ndarray) Array that contains time frequency gain values

        """
        print('Exponential mask')
        self._mask = np.divide(np.log(self._sTarget.clip(self._eps, np.inf)**self._alpha),\
                               np.log(self._nResidual.clip(self._eps, np.inf)**self._alpha))