Multilingual BERT has an accent: Evaluating English influences on fluency in multilingual models

• URL: http://arxiv.org/abs/2210.05619v2
• Date: Thu, 13 Apr 2023 14:59:38 GMT
• Title: Multilingual BERT has an accent: Evaluating English influences on fluency in multilingual models
• Authors: Isabel Papadimitriou, Kezia Lopez, Dan Jurafsky
• Abstract summary: We show that grammatical structures in higher-resource languages bleed into lower-resource languages. We show this bias via a novel method for comparing the fluency of multilingual models to the fluency of monolingual Spanish and Greek models.
• Score: 23.62852626011989
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: While multilingual language models can improve NLP performance on low-resource languages by leveraging higher-resource languages, they also reduce average performance on all languages (the 'curse of multilinguality'). Here we show another problem with multilingual models: grammatical structures in higher-resource languages bleed into lower-resource languages, a phenomenon we call grammatical structure bias. We show this bias via a novel method for comparing the fluency of multilingual models to the fluency of monolingual Spanish and Greek models: testing their preference for two carefully-chosen variable grammatical structures (optional pronoun-drop in Spanish and optional Subject-Verb ordering in Greek). We find that multilingual BERT is biased toward the English-like setting (explicit pronouns and Subject-Verb-Object ordering) as compared to our monolingual control language model. With our case studies, we hope to bring to light the fine-grained ways in which multilingual models can be biased,and encourage more linguistically-aware fluency evaluation.

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