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arXiv · 1810.07931

Unsupervised Neural Text Simplification

Sai Surya·Abhijit Mishra·Anirban Laha·Parag Jain·Karthik Sankaranarayanan
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Abstract

The paper presents a first attempt towards unsupervised neural text simplification that relies only on unlabeled text corpora. The core framework is composed of a shared encoder and a pair of attentional-decoders and gains knowledge of simplification through discrimination based-losses and denoising. The framework is trained using unlabeled text collected from en-Wikipedia dump. Our analysis (both quantitative and qualitative involving human evaluators) on a public test data shows that the proposed model can perform text-simplification at both lexical and syntactic levels, competitive to existing supervised methods. Addition of a few labelled pairs also improves the performance further.

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Sai Surya, Abhijit Mishra, Anirban Laha, Parag Jain, Karthik Sankaranarayanan. 2018-10-18. Unsupervised Neural Text Simplification. https://arxiv.org/abs/1810.07931

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