We investigate prototype-driven learning for primarily unsupervised grammar induction. Prior knowledge is specified declaratively, by providing a few canonical examples of each ta...
Unknown words are a major issue for large-scale grammars of natural language. We propose a machine learning based algorithm for acquiring lexical entries for all forms in the para...
It seems that actual software tools utilizing Computer-Mediated Communication mechanisms -like messaging or chat systems- do not help young students to learn good grammar skills. ...
Corpus-based grammar induction generally relies on hand-parsed training data to learn the structure of the language. Unfortunately, the cost of building large annotated corpora is...
Learning a tree substitution grammar is very challenging due to derivational ambiguity. Our recent approach used a Bayesian non-parametric model to induce good derivations from tr...