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arXiv · 1602.06064

On Training Bi-directional Neural Network Language Model with Noise Contrastive Estimation

Tianxing He·Yu Zhang·Jasha Droppo·Kai Yu
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Abstract

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.

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Tianxing He, Yu Zhang, Jasha Droppo, Kai Yu. 2016-02-19. On Training Bi-directional Neural Network Language Model with Noise Contrastive Estimation. https://arxiv.org/abs/1602.06064

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