A Cross-Linguistic Pressure for Uniform Information Density in Word Order

Published in Transactions of the Association for Computational Linguistics, 2023

Find paper here

While natural languages differ widely in both canonical word order and word order flexibility, their word orders still follow shared cross-linguistic statistical patterns, often attributed to functional pressures. In the effort to identify these pressures, prior work has compared real and counterfactual word orders. Yet one functional pressure has been overlooked in such investigations: the uniform information density (UID) hypothesis, which holds that information should be spread evenly throughout an utterance. Here, we ask whether a pressure for UID may have influenced word order patterns cross-linguistically. To this end, we use computational models to test whether real orders lead to greater information uniformity than counterfactual orders. In our empirical study of 10 typologically diverse languages, we find that: (i) among SVO languages, real word orders consistently have greater uniformity than reverse word orders, and (ii) only linguistically implausible counterfactual orders consistently exceed the uniformity of real orders. These findings are compatible with a pressure for information uniformity in the development and usage of natural languages.

@article{clark-etal-2023-crosslinguistic,
    author = {
        Thomas Hikaru Clark and
        Clara Meister and
        Tiago Pimentel and
        Michael Hahn and
        Ryan Cotterell and
        Richard Futrell and
        Roger Levy
    },
    article = {Transactions of the Association for Computational Linguistics},
    title = {A Cross-Linguistic Pressure for Uniform Information Density in Word Order},
    year = {2023},
    url = {https://aclanthology.org/2023.tacl-1.59/},
    pages = {},
}