Paper Reading AI Learner

Multilingual Synthetic Question and Answer Generation for Cross-Lingual Reading Comprehension

2020-10-22 19:59:37
Siamak Shakeri, Noah Constant, Mihir Sanjay Kale, Linting Xue
arXiv_AI
     
Abstract

We propose a simple method to generate large amounts of multilingual question and answer pairs by a single generative model. These synthetic samples are then applied to augment the available gold multilingual ones to improve the performance of multilingual QA models on target languages. Our approach only requires existence of automatically translated samples from English to the target domain, thus removing the need for human annotations in the target languages. Experimental results show our proposed approach achieves significant gains in a number of multilingual datasets.

Abstract (translated)

URL

https://arxiv.org/abs/2010.12008

PDF

https://arxiv.org/pdf/2010.12008.pdf

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