Abstract

Interpreting is generally recognized as a particularly demanding language processing task for the cognitive system. Dependency distance, the linear distance between two syntactically related words in a sentence, is an index of sentence complexity and is also able to reflect the cognitive constraints during various tasks. In the current research, we examine the difference in dependency distance among three interpreting types, namely, simultaneous interpreting, consecutive interpreting and read-out translated speech based on a treebank comprising these types of interpreting output texts with dependency annotation. Results show that different interpreting renditions yield different dependency distances, and consecutive interpreting texts entail the smallest dependency distance other than those of simultaneous interpreting and read-out translated speech, suggesting that consecutive interpreting bears heavier cognitive demands than simultaneous interpreting. The current research suggests for the first time that interpreting is an extremely demanding cognitive task that can further mediate the dependency distance of output sentences. Such findings may be due to the minimization of dependency distance under cognitive constraints.

Highlights

  • Interpreting, especially simultaneous interpreting (SI), is a demanding language processing task for the cognitive system underpinning language abilities

  • Results from Tukey’s post-hoc tests show that translated speech (TR) has a larger mean dependency distances (MDDs) than both SI (p < 0.001, ηp2 = 0.681) and consecutive interpreting (CI) (p < 0.001, ηp2 = 0.936) and SI has a larger MDD than CI (p < 0.001, ηp2 = 0.555)

  • On the other hand, the significant difference in MDD reveals that the memory load varies in different modes, that is to say, there exists significant difference in terms of the cognitive load among SI, CI, and TR

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Summary

Introduction

Interpreting, especially simultaneous interpreting (SI), is a demanding language processing task for the cognitive system underpinning language abilities Such difficulties include the intensity and continuity of new speech input (Christoffels et al, 2006; Dong and Zhong, 2017), the general temporal overlap (simultaneity) of listening, retaining, comprehending (sometimes referred to as encoding) the input (Seeber and Kerzel, 2011), orally rendering the production, and the conflict and intervening effect of the concurrent activation of two languages (Gerver, 1976; Lambert, 1992; Padilla et al, 1995; Christoffels and De Groot, 2004; Christoffels et al, 2006; Dong and Liu, 2016). The Cognitive Load Model (Seeber, 2011; Seeber and Kerzel, 2011) measures the online memory load generated by the working memory of constituents prior to their integration and/or production through pupil dilation

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