Given a set of phonological features, we can enumerate a set of phonological classes. Here we consider the inverse of this problem: given a set of phonological classes, can we derive a feature system? We show that this is indeed possible, using a collection of algorithms that assign features to a set of input classes and differ in terms of what types of features are permissible. This work bears on theories of both language-specific and universal features, provides testable predictions of the featurizations available to learners, and serves as a useful component in computational models of feature learning.

phonological features, feature learning, underspecification, computational phonology
© 2019 by the Massachusetts Institute of Technology
2019
MIT Press

Supplementary data

Supplemental Appendix

- pdf file

Code Repository (zip archive, 28 KB).

This repository contains the code used in Mayer, C. and Daland, R. (Linguistic Inquiry, Vol. 51, No. 4). A method for projecting features from observed sets of phonological classes. Linguistic Inquiry. This code is made publicly available for use and extension in future research. You can find the most recent version at https://github.com/connormayer/featurizer. The basic functionality of this code is to take a set of input phonological classes and produce a feature system for that set. See the paper for a full description.

- zip file
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