A method, a device, and a non-transitory storage medium are described in which a rehearsal network service is provided that enables generalized learning for all types of input patterns ranging from one-shot inputs to a large set of inputs. The rehearsal network service includes using biological memory indicator data relating to a user and the input data. The rehearsal network service includes calculating a normalized effective salience for each input data, and generating a new set of input data in which the inclusion of input data is proportional to its normalization effective salience. The rehearsal network service further includes augmenting the new set of input data using perturbation values. The rehearsal network service provides the new set of input data to a learning network, such as a neural network or a deep learning network that can learn the user's taste or preference.