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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def masked_middle_map(self):
 """ Return the map from the MFCC speech frame indices in the MIDDLE portion of the wave to the MFCC FULL frame indices. :rtype: :class:`numpy.ndarray` (1D) """

        begin, end = self._masked_middle_begin_end()
        return self.__mfcc_mask_map[begin:end]