ACL Findings2025
Code-Switching and Syntax: A Large-Scale Experiment
Igor Sterner, Simone Teufel
Abstract
The theoretical code-switching (CS) literature provides numerous pointwise investigations that aim to explain patterns in CS, i.e. why bilinguals switch language in certain positions in a sentence more often than in others. A resulting consensus is that CS can be explained by the syntax of the contributing languages. There is however no large-scale, multi-language, cross-phenomena experiment that tests this claim. When designing such an experiment, we need to make sure that the system that is predicting where bilinguals tend to switch has access only to syntactic information. We provide such an experiment here. Results show that syntax alone is sufficient for an automatic system to distinguish between sentences in minimal pairs of CS, to the same degree as bilingual humans. Furthermore, the learnt syntactic patterns generalise well to unseen language pairs.
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Builds on4
- Strategies for Pre-training Graph Neural NetworksWeihua Hu, Bowen Liu, Joseph Gomes, Marinka Zitnik et al.ICLR 2020 · 1,744 citations
- Unsupervised Cross-lingual Representation Learning at ScaleAlexis Conneau, Kartikay Khandelwal, Naman Goyal, Vishrav Chaudhary et al.ACL 2020 · 539 citations
- Segment Any Text: A Universal Approach for Robust, Efficient and Adaptable Sentence SegmentationMarkus Frohmann, Igor Sterner, Ivan Vulic, Benjamin Minixhofer et al.EMNLP 2024 · 10 citations
- Minimal Pair-Based Evaluation of Code-SwitchingIgor Sterner, Simone TeufelACL 2025 · 8 citations
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