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.

翻译：我们提出了一种动态嵌入式主题模型与变点检测的新型组合方法，用于探究古典拉丁语及早期基督教拉丁语中词汇语义模态的历时变化。我们展示了多种方法，用于发现和表征模型输出中的模式，并将其与比较文学与古典学领域的传统学术研究相关联。这种针对语义变化的无监督模型简易方法可适用于任何合适语料库。最后，我们探讨了未来研究方向与改进措施，旨在使噪声更大、整理程度更低的材料也能达到该阈值。