Morphology Matters: A Multilingual Language Modeling Analysis

نویسندگان

چکیده

Abstract Prior studies in multilingual language modeling (e.g., Cotterell et al., 2018; Mielke 2019) disagree on whether or not inflectional morphology makes languages harder to model. We attempt resolve the disagreement and extend those studies. compile a larger corpus of 145 Bible translations 92 number typological features.1 fill missing data for several consider corpus-based measures morphological complexity addition expert-produced features. find that are significantly associated with higher surprisal when LSTM models trained BPE-segmented data. also investigate linguistically motivated subword segmentation strategies like Morfessor Finite-State Transducers (FSTs) these yield better performance reduce impact language’s modeling.

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ژورنال

عنوان ژورنال: Transactions of the Association for Computational Linguistics

سال: 2021

ISSN: ['2307-387X']

DOI: https://doi.org/10.1162/tacl_a_00365