
Approaching explanatory adequacy in phonology using Minimum Description Length
Author(s) -
Ezer Rasin,
Iddo Berger,
Nur Lan,
Itamar Shefi,
Roni Katzir
Publication year - 2021
Publication title -
journal of language modelling
Language(s) - English
Resource type - Journals
eISSN - 2299-856X
pISSN - 2299-8470
DOI - 10.15398/jlm.v9i1.266
Subject(s) - phonology , lexicon , computer science , grammar , linguistics , minimum description length , optimality theory , natural language processing , artificial intelligence , theoretical linguistics , cognitive science , cognitive psychology , psychology , philosophy
A linguistic theory reaches explanatory adequacy if it arrives at a linguistically-appropriate grammar based on the kind of input available to children. In phonology, we assume that children can succeed even when the input consists of surface evidence alone, with no corrections or explicit paradigmatic information – that is, in learning from distributional evidence. We take the grammar to include both a lexicon of underlying representations and a mapping from the lexicon to surface forms. Moreover, this mapping should be able to express optionality and opacity, among other textbook patterns. This learning challenge has not yet been addressed in the literature. We argue that the principle of Minimum Description Length (MDL) offers the right kind of guidance to the learner – favoring generalizations that are neither overly general nor overly specific – and can help the learner overcome the learning challenge. We illustrate with an implemented MDL learner that succeeds in learning various linguistically-relevant patterns from small corpora.