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arXiv:1906.01037cs.CL

Better Character Language Modeling Through Morphology

Terra Blevins, Luke Zettlemoyer

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Abstract

We incorporate morphological supervision into character language models (CLMs) via multitasking and show that this addition improves bits-per-character (BPC) performance across 24 languages, even when the morphology data and language modeling data are disjoint. Analyzing the CLMs shows that inflected words benefit more from explicitly modeling morphology than uninflected words, and that morphological supervision improves performance even as the amount of language modeling data grows. We then transfer morphological supervision across languages to improve language modeling performance in the low-resource setting.

arXiv comments
Accepted to ACL 2019
Journal reference
DOI
Subjects
cs.CLComputation and Language

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