Automatically Paraphrasing via Sentence Reconstruction and Round-trip Translation
Automatically Paraphrasing via Sentence Reconstruction and Round-trip Translation
Zilu Guo, Zhongqiang Huang, Kenny Q. Zhu, Guandan Chen, Kaibo Zhang, Boxing Chen, Fei Huang
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence
Main Track. Pages 3815-3821.
https://doi.org/10.24963/ijcai.2021/525
Paraphrase generation plays key roles in NLP tasks such as question answering, machine translation, and information retrieval. In this paper, we propose a novel framework for paraphrase generation. It simultaneously decodes the output sentence using a pretrained wordset-to-sequence model and a round-trip translation model. We evaluate this framework on Quora, WikiAnswers, MSCOCO and Twitter, and show its advantage over previous state-of-the-art unsupervised methods and distantly-supervised methods by significant margins on all datasets. For Quora and WikiAnswers, our framework even performs better than some strongly supervised methods with domain adaptation. Further, we show that the generated paraphrases can be used to augment the training data for machine translation to achieve substantial improvements.
Keywords:
Natural Language Processing: Machine Translation
Natural Language Processing: Natural Language Generation
Natural Language Processing: NLP Applications and Tools