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  • Author or Editor: Binghan Zheng x
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This paper aims to examine gender differences in hedging in Chinese–English conference interpreting based on a transcribed parallel corpus. The point of departure was to test Holmes’s (1986, 1988a) claims that women do not necessarily employ more hedges than men but that women’s use of hedges tends to focus more on interpersonal relationships while men’s is more on propositional precision. Hyland’s (1996a, 1996b) model in which hedges were categorized into accuracy-oriented, speaker-oriented and audience-oriented, has been adapted for this end. Our finding shows that male interpreters actually employ more hedges than their female counterparts on the whole. In particular, their accuracy-oriented and speaker-oriented hedges exceed those of female interpreters, but not for audience-oriented ones. To find out whether these differences were caused by the source texts per se or by interpreters’ manipulation, we named four types of interpreting approach towards hedge items: direct transfer, indirect transfer, shift and addition. The former two types were identified as source text interference while the latter two as interpreters’ manipulation. The results indicate that male interpreters exceed female interpreters in terms of shift and addition cases in all three types of hedges. The findings of the present study contribute to a more profound understanding of gender difference in language mediation and also have implications for future interpreter training.

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Abstract

This study explores the interaction effect between source text (ST) complexity and machine translation (MT) quality on the task difficulty of neural machine translation (NMT) post-editing from English to Chinese. When investigating human effort exerted in post-editing, existing studies have seldom taken both ST complexity and MT quality levels into account, and have mainly focused on MT systems used before the emergence of NMT. Drawing on process and product data of post-editing from 60 trainee translators, this study adopted a multi-method approach to measure post-editing task difficulty, including eye-tracking, keystroke logging, quality evaluation, subjective rating, and retrospective written protocols. The results show that: 1) ST complexity and MT quality present a significant interaction effect on task difficulty of NMT post-editing; 2) ST complexity level has a positive impact on post-editing low-quality NMT (i.e., post-editing task becomes less difficult when ST complexity decreases); while for post-editing high-quality NMT, it has a positive impact only on the subjective ratings received from participants; and 3) NMT quality has a negative impact on its post-editing task difficulty (i.e., the post-editing task becomes less difficult when MT quality goes higher), and this impact becomes stronger when ST complexity increases. This paper concludes that both ST complexity and MT quality should be considered when testing post-editing difficulty, designing tasks for post-editor training, and setting fair post-editing pricing schemes.

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