Lin Yumeng, Liang Junying
Department of Linguistics, Zhejiang University, 866 Yuhangtang Road, Hangzhou 310058, China.
Entropy (Basel). 2023 Jan 28;25(2):243. doi: 10.3390/e25020243.
Previous quantitative studies discussing interpreting types have focused on various features of linguistic forms in outputs. However, none of them has examined their informativeness. Entropy, as a measure of the average information content and the uniformity of the probability distribution of language units, has been applied to quantitative linguistic research on different types of language texts. In the present study, entropy and repeat rate were used to investigate the difference of overall informativeness and concentration of output texts between simultaneous interpreting and consecutive interpreting. We intend to figure out the frequency distribution patterns of word and word category in two types of interpreting texts. Analyses of linear mixed-effects models showed that entropy and repeat rate can distinguish the informativeness of consecutive and simultaneous interpreting outputs, and consecutive interpreting outputs entail a higher word entropy value and a lower word repeat rate than simultaneous interpreting outputs. We propose that consecutive interpreting is a cognitive process which reaches an equilibrium between production economy for interpreters and comprehension sufficiency for listeners, especially in the case where input speeches are more complex. Our findings also shed lights on the selection of interpreting types in application scenarios. The current research is the first of its kind in examining informativeness across interpreting types, demonstrating a dynamic adaptation of language users to extreme cognitive load.
以往讨论口译类型的定量研究主要关注产出中语言形式的各种特征。然而,它们都没有考察其信息性。熵作为衡量语言单位平均信息含量和概率分布均匀性的指标,已被应用于不同类型语言文本的定量语言学研究。在本研究中,熵和重复率被用来研究同声传译和交替传译产出文本的整体信息性和集中度的差异。我们旨在找出两种口译文本中单词和词类的频率分布模式。线性混合效应模型分析表明,熵和重复率可以区分交替传译和同声传译产出的信息性,交替传译产出的单词熵值高于同声传译产出,单词重复率低于同声传译产出。我们认为,交替传译是一个在口译员的产出经济性和听众的理解充分性之间达到平衡的认知过程,尤其是在输入演讲较为复杂的情况下。我们的研究结果也为应用场景中口译类型的选择提供了启示。当前的研究是首次跨口译类型考察信息性,展示了语言使用者对极端认知负荷的动态适应。