论文标题
礼貌转移：标签和生成方法
Politeness Transfer: A Tag and Generate Approach
论文作者
论文摘要
本文介绍了一项新的礼貌转移任务，其中涉及将非政治句子转换为礼貌的句子，同时保留含义。我们还提供了一个超过1.39个实例的数据集，自动标记为礼貌，以鼓励对这项新任务进行基准评估。我们设计一个标签并生成管道，该管道可以识别风格属性，然后以目标样式生成句子，同时保留大多数源内容。对于礼貌和其他五项转移任务，我们的模型在自动指标上的最新方法优于内容保存的最新方法，其样式转移精度具有可比或更好的性能。此外，我们的模型超过了有关人类评估语法性的现有方法，这意味着在所有六个样式转移任务中保存和转移精度。数据和代码位于https://github.com/tag-and-generate上。
This paper introduces a new task of politeness transfer which involves converting non-polite sentences to polite sentences while preserving the meaning. We also provide a dataset of more than 1.39 instances automatically labeled for politeness to encourage benchmark evaluations on this new task. We design a tag and generate pipeline that identifies stylistic attributes and subsequently generates a sentence in the target style while preserving most of the source content. For politeness as well as five other transfer tasks, our model outperforms the state-of-the-art methods on automatic metrics for content preservation, with a comparable or better performance on style transfer accuracy. Additionally, our model surpasses existing methods on human evaluations for grammaticality, meaning preservation and transfer accuracy across all the six style transfer tasks. The data and code is located at https://github.com/tag-and-generate.
