title: Realizing the Now-or-Never bottleneck and Chunk-and-Pass processing with Item-Order-Rank working memories and masking field chunking networks.
abstract: Christiansen & Chater's (C&C's) key goals for a language system have been realized by neural models for short-term storage of linguistic items in an Item-Order-Rank working memory, which inputs to Masking Fields that rapidly learn to categorize, or chunk, variable-length linguistic sequences, and choose the contextually most predictive list chunks while linguistic inputs are stored in the working memory.
authors: Center for Adaptive Systems,Boston University,Boston,MA 02215.steve@bu.eduhttp://cns.bu.edu/~steve.
authors: Stephen
authors: S
authors: Grossberg
mesh_terms: D006801:Humans; D007802:Language; D007858:Learning; D008570:Memory, Short-Term