We present a novel combination of dynamic embedded topic models and
change-point detection to explore diachronic change of lexical semantic
modality in classical and early Christian Latin. We demonstrate several methods
for finding and characterizing patterns in the output, and relating them to
traditional scholarship in Comparative Literature and Classics. This simple
approach to unsupervised models of semantic change can be applied to any
suitable corpus, and we conclude with future directions and refinements aiming
to allow noisier, less-curated materials to meet that threshold.

我们提出了一种新颖的动态嵌入式主题模型和转折点检测的组合方法，用于探索古典与早期基督教拉丁语中词汇语义情态的历时变化。我们展示了几种方法来寻找和描述产出中的模式，并将其与比较文学和经典学中的传统学术研究联系起来。这种简单的无监督语义变化模型方法可以应用于任何合适的语料库，我们最后讨论了未来的方向和改进，以使噪声更大、经过整理较少的材料达到这个阈值。