Zero-shot Domain Adaptation for Neural Machine Translation with Retrieved Phrase-level Prompts

09/23/2022
by   Zewei Sun, et al.
0

Domain adaptation is an important challenge for neural machine translation. However, the traditional fine-tuning solution requires multiple extra training and yields a high cost. In this paper, we propose a non-tuning paradigm, resolving domain adaptation with a prompt-based method. Specifically, we construct a bilingual phrase-level database and retrieve relevant pairs from it as a prompt for the input sentences. By utilizing Retrieved Phrase-level Prompts (RePP), we effectively boost the translation quality. Experiments show that our method improves domain-specific machine translation for 6.2 BLEU scores and improves translation constraints for 11.5 additional training.

READ FULL TEXT

Please sign up or login with your details

Forgot password? Click here to reset