Parallel Data Augmentation for Formality Style Transfer
Table 6: Performances of formality discrimination based on different pivot languages: French (Fr), German (De) and Chinese (Zh).
['[BOLD] Model', '[BOLD] E&M', '[BOLD] F&R']
Manual inspection reveals that a few pairs have the issue of meaning inconsistency in all the three sets, which mainly arises from the translation difficulties caused by omissions and poor grammaticality in informal sentences and the segmentation ambiguity in some pivot languages like Chinese. Among the three languages, the Chinese-based augmented data introduces more noise due to the additional segmentation ambiguity problem but brings fair improvement because of its largest size. In contrast, the German-based augmented data has relatively high quality and a moderate size, leading to the best result in our experiments.