Tim O’Donnell in Leiden

Tim O’Donnell was in Leiden last week for the The Comparative Biology of Language Learning workshop, held at the Lorentz Center April 3–7. He gave a talk Thursday, title and abstract below:

Bayesian Program Learning of Morphophonological Rules

Both children and linguists confront a similar problem of inference:

given utterances produced by speakers, together with aspects of the

meaning of those utterances, discover the grammatical principles that

relate form to meaning. We study this abstract computational problem

within the domain of morphophonology, contributing a computational

model that learns phenomena from many natural languages and

generalizes in humanlike ways from data used in behavioral studies of

artificial grammar learning.

Our work draws on two analogies. The child-as-linguist analogy holds

that both children and linguists must solve the same abstract

inductive reasoning problem, even though the nature of the input data

and underlying mental algorithms are surely different in precise

detail. Accordingly we isolate the problem of learning

morphophonological systems, and show that a single solution to this

problem can capture both linguistic analyses from natural languages

and infant rule learning of artificial languages. We adopt the

framework of “Bayesian Program learning” (BPL) – in which learning is

formulated a synthesizing a program which compactly describes the

input data. This learning-as-programming analogy lets us exploit

recent techniques from the field of program synthesis to induce

morphophonological rules from data. While child-as-linguist poses the

computational problem, learning-as-programming offers a solution.