🤖 AI Summary
This study addresses the limitation of existing lexical semantic change research, which quantifies magnitude but lacks explanatory power regarding timing, mechanisms, and attribution. To bridge this gap, we propose CUSP, a framework that couples usage and meaning processes to unify change magnitude, timing, mechanisms, displacement patterns, and textual evidence within a single historical perspective. Methodologically, CUSP integrates hierarchical coupling, Markov composition, displacement operators, and Gaussian mixture model parameter recovery techniques. Experimental evaluations demonstrate that the proposed framework maintains competitive performance on the DWUG benchmark while successfully elucidating fine-grained semantic evolution in English and German corpora, as well as in U.S. court opinions.
📝 Abstract
Lexical semantic change is usually summarized by a scalar distance between independently sampled period distributions. This measures how much a word changed, but does not reveal when it changed, which mechanisms and component movements carried the change, or which usages support the attribution. We introduce Coupled Usage--Sense Processes (CUSP), which derives these answers from a single marginal preserving temporal process. A hierarchical coupling relates contextual distributions through latent usage components, while Markov composition makes adjacent and longer span correspondences compatible. Displacement operators quantify change magnitude and timing, split variation exactly between movement of component centers and reorganization within components, and attribute it to transported component pairs. Word-local modes resolve distinct directions of change and their activity over time, while representative passages from attributed components ground the analysis in text. Under a Gaussian mixture specialization, we prove parametric recovery of the operators and squared distances. Synthetic experiments support the predicted rate. CUSP remains competitive on English and German DWUG and recovers controlled Janus profiles while maintaining compositionally coherent transport. A large corpus of US court opinions demonstrates transition, mode, and passage attribution in unlabeled natural text. CUSP thus makes magnitude, timing, mechanism, movement, modes, and textual evidence compatible views of one lexical history.