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Cross-lingual transfer between a high-resource language and its dialects orclosely related language varieties should be facilitated by their similarity.However, current approaches that operate in the embedding space do not takesurface similarity into account. This work presents a simple yet effectivestrategy to imrove cross-lingual transfer between closely related varieties. Wepropose to augment the data of the high-resource source language withcharacter-level noise to make the model more robust towards spellingvariations. Our strategy shows consistent improvements over several languagesand tasks: Zero-shot transfer of POS tagging and topic identification betweenlanguage varieties from the Finnic, West and North Germanic, and WesternRomance language branches. Our work provides evidence for the usefulness ofsimple surface-level noise in improving transfer between language varieties.

Improving Zero-shot Cross-lingual Transfer between Closely Related Languages by injecting Character-level Noise