  We propose to train bi-directional neural network language model(NNLM) with
noise contrastive estimation(NCE). Experiments are conducted on a rescore task
on the PTB data set. It is shown that NCE-trained bi-directional NNLM
outperformed the one trained by conventional maximum likelihood training. But
still(regretfully), it did not out-perform the baseline uni-directional NNLM.
