Using character N-grams to explorediachronic change in medieval English

Author:

Buckley Kevin1,Vogel Carl2

Affiliation:

1. School of Modern Languages, Newcastle University , Newcastle upon Tyne , UK

2. Trinity Centre for Computing and Language Studies, Computational Linguistics Group, School of Computer Science and Statistics , Trinity College Dublin, the University of Dublin , Dublin , Ireland

Abstract

Abstract This paper applies character N-grams to the study of diachronic linguistic variation in a historical language. The period selected for this initial exploratory study is medieval English, a well-studied period of great linguistic variation and language contact, whereby the efficacy of computational techniques can be examined through comparison to the wealth of thorough scholarship on medieval linguistic variation. Frequency profiles of character N-gram features were generated for several epochs in the history of English and a measure of language distance was employed to quantify the similarity between English at different stages in its history. Through this a quantification of internal change in English was achieved. Furthermore similarity between English and other medieval languages across time was measured allowing for a measurement of the well-known period of contact between English and Anglo-Norman French. This methodology is compared to traditional lexicostatistical methods and shown to be able to derive the same patterns as those derived from expert-created feature lists (i.e. Swadesh lists). The use of character N-gram profiles proved to be a flexible and useful method to study diachronic variation, allowing for the highlighting of relevant features of change. This method may be a complement to traditional qualitative examinations.

Publisher

Walter de Gruyter GmbH

Subject

Linguistics and Language,Language and Linguistics

Reference66 articles.

1. Alcorn, Rhona, Robert Truswell, Joel Wallenberg & James Donaldson. 2018. A parsed linguistic atlas of early middle English. https://datashare.is.ed.ac.uk/handle/10283/3032 (accessed April 2018).

2. Baker, Peter S. 2012. Introduction to old English, 3rd edn. Oxford: Wiley-Blackwell.

3. Benoit, Kenneth & Paul Nulty. 2013. Quanteda: Quantitative analysis of Textual Data, An R library for managing and analyzing text.

4. Borin, Lars. 2013. The why and how of measuring linguistic differences. Approaches to measuring linguistic differences, 3–25. Berlin: Walter de Gruyter.

5. Borin, Lars, Bernard Comrie & Anju Saxena. 2013. The intercontinental dictionary series—A rich and principled database for language comparison. Approaches to measuring linguistic differences, 285–302. Berlin: Walter de Gruyter.

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