Vector Space Morphology with Linear Discriminative Learning

Abstract

This chapter presents three case studies of modeling aspects of lexical processing with Linear Discriminative Learning (LDL), the computational engine of the Discriminative Lexicon model. With numeric representations of word forms and meanings, LDL learns to map one vector space onto the other, without being informed about any morphological structure or inflectional classes. The modeling results demonstrated that LDL not only performs well for understanding and producing morphologically complex words, but that it also generates quantitative measures that are predictive for human behavioral data.