Morphological Irregularity Correlates with Frequency

39457

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nan

Abstract

AbstractWe present a study of morphological irregularity. Following recent work, we define an information-theoretic measure of irregularity based on the predictability of forms in a language. Using a neural transduction model, we estimate this quantity for the forms in 28 languages. We first present several validatory and exploratory analyses of irregularity. We then show that our analyses provide evidence for a correlation between irregularity and frequency: higher frequency items are more likely to be irregular and irregular items are more likely be highly frequent. To our knowledge, this result is the first of its breadth and confirms longstanding proposals from the linguistics literature. The correlation is more robust when aggregated at the level of whole paradigms—providing support for models of linguistic structure in which inflected forms are unified by abstract underlying stems or lexemes.

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Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pages 5117–5126 Florence, Italy, July 28 - August 2, 2019. c⃝2019 Association for Computational Linguistics 5117 Morphological Irregularity Correlates with Frequency Shijie Wu Department of Computer Science Johns Hopkins University Baltimore, US shijie.wu@jhu.edu Ryan Cotterell The Computer Laboratory University of Cambridge Cambridge, UK rdc42@cam.ac.uk Timothy J. O’Donnell Department of Linguistics McGill University Montr´eal, Canada timothy.odonnell@mcgill.ca Abstract We present a study of morphological irregu- larity. Following recent work, we define an information-theoretic measure of irregularity based on the predictability of forms in a lan- guage. Using a neural transduction model, we estimate this quantity for the forms in 28 languages. We first present several val- idatory and exploratory analyses of irregular- ity. We then show that our analyses provide evidence for a correlation between irregular- ity and frequency: higher frequency items are more likely to be irregular and irregular items are more likely be highly frequent. To our knowledge, this result is the first of its breadth and confirms longstanding proposals from the linguistics literature. The correla- tion is more robust when aggregated at the level of whole paradigms—providing support for models of linguistic structure in which in- flected forms are unified by abstract under- lying stems or lexemes. Code is available at https://github.com/shijie-wu/ neural-transducer. 1 Introduction Irregularity is a pervasive phenomenon in the in- flectional morphology of the world’s languages and raises a number of questions about language design, learnability, and change. Nevertheless, irregularity remains an understudied phenomenon and many basic questions remain unanswered (Kiefer, 2000; Stolz et al., 2012). Do all languages exhibit irregu- larity? What is the relationship between irregularity and frequency? Is irregularity best thought of as a property of individual forms, or a property of more abstract objects like morphological paradigms? In this paper, we examine these questions, focusing in particular on the relationship between irregularity and frequency. One of the fundamental challenges in studying ir- regularity is defining the phenomenon in a way that is applicable across languages. We begin the paper by addressing this question. First, we formalize the problem of inflectional morphology and present a novel, information-theoretic measure of the degree of irregularity of an inflected form. This definition builds on recent work that defines (ir)regularity in terms of the probabilistic predictability of a form given the rest of the language (Cotterell et al., 2018a; Ackerman and Malouf, 2013). Making use of a state-of-the-art model of morphological inflec- tion, we estimate our measure of irregularity across a large number of word forms from 28 languages drawn from the UniMorph database (Kirov et al., 2018). Based on these estimates we perform three studies. First, we validate our estimates by exam- ining the predictions on English past tense forms— showing that the model’s predicts accord with hu- man judgements of irregularity. We also examine the overall rate of accuracy of our model. Second, we examine the degree of irregularity across lan- guages, showing that the model predicts wide vari- ance in the average …

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Labeled Text

AbstractWe present a study of morphological irregularity. Following recent work, we define an information-theoretic measure of irregularity based on the predictability of forms in a language. Using a neural transduction model, we estimate this quantity for the forms in 28 languages. We first present several validatory and exploratory analyses of irregularity. We then show that our analyses provide evidence for a correlation between irregularity and frequency: higher frequency items are more likely to be irregular and irregular items are more likely be highly frequent. To our knowledge, this result is the first of its breadth and confirms longstanding proposals from the linguistics literature. The correlation is more robust when aggregated at the level of whole paradigms—providing support for models of linguistic structure in which inflected forms are unified by abstract underlying stems or lexemes.

Publication Details

Paper ID:
39457
Year:
2019
Publication:
TIPSTER
Publication Type:
conf
DOI:
nan