SilverAlign：一种基于MT的Silver数据词对齐评价算法
SilverAlign: MT-Based Silver Data Algorithm For Evaluating Word Alignment
摘要：
单词对齐对于各种NLP任务至关重要。因此，选择最佳的创建方法至关重要。然而，黄金评估数据的稀缺性使选择变得困难。我们提出了SilverAlign，一种新的方法来自动创建银数据的评价字对齐器，利用机器翻译和最小对。我们表明，银数据的性能与9种语言对的黄金基准相关，使我们的方法成为在黄金数据不可用时评估不同领域和语言的有效资源。这解决了低资源语言缺少黄金数据对齐的重要情况。
英文摘要：
Word alignments are essential for a variety of NLP tasks. Therefore, choosing the best approaches for their creation is crucial. However, the scarce availability of gold evaluation data makes the choice difficult. We propose SilverAlign, a new method to automatically create silver data for the evaluation of word aligners by exploiting machine translation and minimal pairs. We show that performance on our silver data correlates well with gold benchmarks for 9 language pairs, making our approach a valid resource for evaluation of different domains and languages when gold data are not available. This addresses the important scenario of missing gold data alignments for low-resource languages.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
