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A comparison between morphological complexity measures: typological data vs. language corpora

  • Language complexity is an intriguing phenomenon argued to play an important role in both language learning and processing. The need to compare languages with regard to their complexity resulted in a multitude of approaches and methods, ranging from accounts targeting specific structural features to global quantification of variation more generally. In this paper, we investigate the degree to which morphological complexity measures are mutually correlated in a sample of more than 500 languages of 101 language families. We use human expert judgements from the World Atlas of Language Structures (WALS), and compare them to four quantitative measures automatically calculated from language corpora. These consist of three previously defined corpus-derived measures, which are all monolingual, and one new measure based on automatic word-alignment across pairs of languages. We find strong correlations between all the measures, illustrating that both expert judgements and automated approaches converge to similar complexity ratings, and can be used interchangeably.

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Author:Christian Bentz, Tatjana Soldatova, Alexander KoplenigGND, Tanja Samardžić
Parent Title (English):Proceedings of the Workshop on Computational Linguistics for Linguistic Complexity (CL4LC). Osaka, Japan, December 11-17 2016. As a part of Coling 2016. 26th International Conference on Computational Linguistics
Document Type:Conference Proceeding
Year of first Publication:2016
Date of Publication (online):2016/10/26
First Page:142
Last Page:153
Licence (German):Es gilt das UrhG