3 papers
cs.CL2024
Detecting Structured Language Alternations in Historical Documents by Combining Language Identification with Fourier Analysis
Hale Sirin, Sabrina Li, Tom Lippincott
In this study, we present a generalizable workflow to identify documents in a historic language with a nonstandard language and script combination, Armeno-Turkish. We introduce the…
cs.CL2024
Dynamic embedded topic models and change-point detection for exploring literary-historical hypotheses
Hale Sirin, Tom Lippincott
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 Christia…
cs.LG2024
Graph-Convolutional Autoencoder Ensembles for the Humanities, Illustrated with a Study of the American Slave Trade
Tom Lippincott
We introduce a graph-aware autoencoder ensemble framework, with associated formalisms and tooling, designed to facilitate deep learning for scholarship in the humanities. By compos…