论文标题
在线与离线NMT质量：对英语 - 德语和德语英语的深入分析
Online Versus Offline NMT Quality: An In-depth Analysis on English-German and German-English
论文作者
论文摘要
我们在这项工作中进行了一项评估研究，比较离线和在线神经机器翻译体系结构。两个序列到序列模型：卷积普遍的注意力（Elbayad等，2018）和基于注意力的变压器（Vaswani等人，2017年）。对于这两种架构，我们通过对英语 - 德语和德语 - 英语配对的精心设计的人类评估对在线解码约束对翻译质量的影响，后者对延迟约束特别敏感。评估结果使我们能够在转移到在线设置时确定每个模型的优势和缺点。
We conduct in this work an evaluation study comparing offline and online neural machine translation architectures. Two sequence-to-sequence models: convolutional Pervasive Attention (Elbayad et al. 2018) and attention-based Transformer (Vaswani et al. 2017) are considered. We investigate, for both architectures, the impact of online decoding constraints on the translation quality through a carefully designed human evaluation on English-German and German-English language pairs, the latter being particularly sensitive to latency constraints. The evaluation results allow us to identify the strengths and shortcomings of each model when we shift to the online setup.
