Diverse Embedding Neural Network Language Models

Kartik Audhkhasi; Abhinav Sethy; Bhuvana Ramabhadran

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arXiv · 1412.7063

Diverse Embedding Neural Network Language Models

Kartik Audhkhasi·Abhinav Sethy·Bhuvana Ramabhadran

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Abstract

We propose Diverse Embedding Neural Network (DENN), a novel architecture for language models (LMs). A DENNLM projects the input word history vector onto multiple diverse low-dimensional sub-spaces instead of a single higher-dimensional sub-space as in conventional feed-forward neural network LMs. We encourage these sub-spaces to be diverse during network training through an augmented loss function. Our language modeling experiments on the Penn Treebank data set show the performance benefit of using a DENNLM.

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Kartik Audhkhasi, Abhinav Sethy, Bhuvana Ramabhadran. 2014-12-22. Diverse Embedding Neural Network Language Models. https://arxiv.org/abs/1412.7063

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