Disentangling dialects: a neural approach to Indo-Aryan historical phonology and subgrouping
Chundra Cathcart, Taraka Rama · 2020
This paper seeks to uncover patterns of sound change across Indo-Aryan languages using an LSTM encoder-decoder architecture.We augment our models with embeddings representing language ID, part of speech, and other features such as word embeddings.We find that a highly augmented model shows highest accuracy in predicting held-out forms, and investigate other properties of interest learned by our models' representations.We outline extensions to this architecture that can better capture variation in Indo-Aryan sound change.