How to Choose Successful Losers in Error-Driven Phonotactic Learning
Giorgio Magri, René Kager · 2015
An error-driven phonotactic learner is trained on a stream of licit phonological forms.Each piece of training data counts as a winner in terms of Optimality Theory.In order to test its current grammar, the learner needs to compare the current winner with a properly chosen loser.This paper advocates a new subroutine for the choice of the loser, based on the idea of minimizing the "distance" from the given winner.