Naively assuming English as a source language may hinder cross-lingual
transfer for many languages by failing to consider the importance of language
contact. Some languages are more well-connected than others, and target
languages can benefit from transferring from closely related languages; for
many languages, the set of closely related languages does not include English.
In this work, we study the impact of source language for cross-lingual
transfer, demonstrating the importance of selecting source languages that have
high contact with the target language. We also construct a novel benchmark
dataset for close contact Chinese-Japanese-Korean-Vietnamese (CJKV) languages
to further encourage in-depth studies of language contact. To comprehensively
capture contact between these languages, we propose to integrate Romanized
transcription beyond textual scripts via Contrastive Learning objectives,
leading to enhanced cross-lingual representations and effective zero-shot
cross-lingual transfer.

通过考虑语言接触的重要性，本研究研究了源语言对跨语言转移的影响，并提出了一种整合罗马化转录的方法来增强跨语言表示和有效的零样本跨语言转移，进而鼓励对接触语言的深入研究。