Since the neural networks can be near-perfect nonlinear function approximators (Liang and Srikant, 2016), we can expect an NAR model to learn the AR translation process quite well, as long as the model has enough capacity.
we first obtain the greedy output of a trained AR model, and use the resulting paired data to train the NAR model.