This document describes the findings of the Third Workshop on Neural Generation and Translation, held in concert with the annual conference of the Empirical Methods in Natural Language Processing (EMNLP 2019). First, we summarize the research trends of papers presented in the proceedings. Second, we describe the results of the two shared tasks 1) efficient neural machine translation (NMT) where participants were tasked with creating NMT systems that are both accurate and efficient, and 2) document-level generation and translation (DGT) where participants were tasked with developing systems that generate summaries from structured data, potentially with assistance from text in another language.
翻译:本文件介绍了与自然语言处理经验方法年度会议(EMNLP 2019)联合举行的第三次神经生成和翻译讲习班的结论。首先,我们总结了在议事录中提出的论文的研究趋势。第二,我们描述了两项共同任务的结果:(1) 高效神经机器翻译(NMT),其中参与者的任务是建立准确和高效的NMT系统;和(2) 文件级生成和翻译(DGT),其中参与者的任务是开发系统,利用结构化数据产生摘要,并有可能借助另一种语言的文本。