A Connectionist Learning Approach to Analyzing Linguistic Stress

Part of Advances in Neural Information Processing Systems 4 (NIPS 1991)

Bibtex Metadata Paper


Prahlad Gupta, David Touretzky


We use connectionist modeling to develop an analysis of stress systems in terms of ease of learnability. In traditional linguistic analyses, learnability arguments determine default parameter settings based on the feasibilty of logicall y deducing correct settings from an initial state. Our approach provides an empirical alter(cid:173) native to such arguments. Based on perceptron learning experiments using data from nineteen human languages, we develop a novel characterization of stress patterns in terms of six parameters. These provide both a partial description of the stress pattern itself and a prediction of its learnability, without invoking abstract theoretical constructs such as metrical feet. This work demonstrates that ma(cid:173) chine learning methods can provide a fresh approach to understanding linguistic phenomena.


The domain of stress systems in language is considered to have a relatively good linguistic theory, called metrical phonologyl. In this theory, the stress patterns of many languages can be described concisely, and characterized in terms of a set of linguistic "parameters," such as bounded vs. unbounded metrical feet, left vs. right dominant feet, etc.2 In many languages, stress tends to be placed on certain kinds of syllables rather than on others; the former are termed heavy syllables, and the latter light syllables. Languages that distinguish

lFor an overview of the theory, see [Goldsmith 90, chapter 4]. 2See [Dresher 90] for one such parameter scheme.