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Proceedings of the Workshop on Methods for Optimizing and Evaluating Neural Language Generation
Semi-supervised learning is an efficient way to improve performance for natural language processing systems. In this work, we propose Para-SSL, a scheme to generate candidate utterances using paraphrasing and methods from semi-supervised learning. In order to perform paraphrase generation in the context of a dialog system, we automatically extract paraphrase pairs to create a paraphrase corpus. Using this data, we build a paraphrase generation system and perform one-to-many generation, followeddoi:10.18653/v1/w19-2306 fatcat:scrsvohq6vhwrbos6hoa7swm3u