A Second Language Acquisition Model Using Example Generalization and Concept Categories
We present a computational model of acquiring a second language from example sentences. Our learning algorithms build a construction grammar language model, and generalize using form-based patterns and the learner’s conceptual system. We use a unique professional language learning corpus, and show that substantial reliable learning can be achieved even though the corpus is very small. The model is applied to assisting the authoring of Japanese language learning corpora.