SiniticMTError: A Machine Translation Dataset with Error Annotations for Sinitic Languages

Hannah Liu

Keywords: Machine Translation, Sinitic Languages, Low-resource languages, multilinguality

Abstract: Despite major advances in machine translation (MT) in recent years, progress remains limited for many low-resource languages that lack large-scale training data and linguistic resources. Cantonese and Wu Chinese are two Sinitic examples, although each enjoys more than 80 million speakers around the world. Thus, we introduce SiniticMTError, a novel dataset that builds on existing parallel corpora to provide error span, error type, and error severity annotations in machine-translated examples from English to Mandarin, Cantonese, and Wu Chinese.

Submission Number: 214