title: Reservoir computing and the Sooner-is-Better bottleneck.
abstract: Prior language input is not lost but integrated with the current input. This principle is demonstrated by "reservoir computing": Untrained recurrent neural networks project input sequences onto a random point in high-dimensional state space. Earlier inputs can be retrieved from this projection, albeit less reliably so as more input is received. The bottleneck is therefore not "Now-or-Never" but "Sooner-is-Better."
authors: Centre for Language Studies,Radboud University Nijmegen,6500 HD Nijmegen,The Netherlands.s.frank@let.ru.nlwww.stefanfrank.info.
authors: Stefan L
authors: SL
authors: Frank
authors: Max Planck Institute for Psycholinguistics,6500 AH Nijmegen,The Netherlands.hartmut.fitz@mpi.nlwww.mpi.nl/people/fitz-hartmut.
authors: Hartmut
authors: H
authors: Fitz
mesh_terms: D006801:Humans; D007802:Language; D016571:Neural Networks, Computer