Linguistic Distance

Linguistic distance quantifies the degree of similarity or difference between languages, focusing on aspects like phonology, morphology, syntax, and lexicon. Current research investigates how this distance impacts cross-lingual transfer in machine learning models, exploring the relationship between linguistic features and model performance using techniques like Bayesian noise processes and information-theoretic measures applied to word embeddings and parts-of-speech distributions. Understanding linguistic distance is crucial for improving the robustness and generalization capabilities of multilingual language models and for developing more accurate assessments of language proficiency and cross-cultural communication.