CODET: A Benchmark for Contrastive Dialectal Evaluation of Machine Translation

Neural machine translation (NMT) systems exhibit limited robustness in handling source-side linguistic variations. Their performance tends to degrade when faced with even slight deviations in language usage, such as different domains or variations introduced by second-language speakers. It is intuitive to extend this observation to encompass dialectal variations as well, but the work allowing the community to evaluate MT systems on this dimension is limited. To alleviate this issue, we compile and release CODET, a contrastive dialectal benchmark encompassing 891 …

benchmark cs.cl domains evaluation language machine machine translation neural machine translation observation performance robustness speakers systems translation usage