Some Tests of an Unsupervised Model of Language Acquisition

We outline an unsupervised language acquisition algorithm and offer some psycholinguistic support for a model based on it. Our approach resem- bles the Construction Grammar in its general phi- losophy, and the Tree Adjoining Grammar in its computational characteristics. The model is trained on a corpus of transcribed child-directed speech (CHILDES). The model's ability to process novel inputs makes it capable of taking various standard tests of English that rely on forced-choice judgment and on magnitude estimation of linguistic accept- ability. We report encouraging results from several such tests, and discuss the limitations revealed by other tests in our present method of dealing with novel stimuli.