Incremental Grammar Induction from Child-Directed Dialogue Utterances

Abstract

We describe a method for learning an incremental semantic grammar from data in which utterances are paired with logical forms representing their meaning. Work- ing in an inherently incremental framework, Dynamic Syntax, we show how words can be associated with probabilistic procedures for the incremental projection of meaning, providing a grammar which can be used directly in incremental prob- abilistic parsing and generation. We test this on child-directed utterances from the CHILDES corpus, and show that it results in good coverage and semantic accuracy, without requiring annotation at the word level or any independent notion of syntax