  This paper uses a novel data-driven probabilistic approach to address the
century-old Inner-Outer hypothesis of Indo-Aryan. I develop a Bayesian
hierarchical mixed-membership model to assess the validity of this hypothesis
using a large data set of automatically extracted sound changes operating
between Old Indo-Aryan and Modern Indo-Aryan speech varieties. I employ
different prior distributions in order to model sound change, one of which, the
logistic normal distribution, has not received much attention in linguistics
outside of Natural Language Processing, despite its many attractive features. I
find evidence for cohesive dialect groups that have made their imprint on
contemporary Indo-Aryan languages, and find that when a logistic normal prior
is used, the distribution of dialect components across languages is largely
compatible with a core-periphery pattern similar to that proposed under the
Inner-Outer hypothesis.
