Interpreting as a mirror for language foundations: Comment on "Rethinking foundations of language from a multidisciplinary perspective" by T. Gong et al

Assessing mental demand in consecutive interpreting: Insights from an fNIRS study

Consecutive interpreting involves a demanding language task where mental workload (MWL) is crucial for assessing interpreters' performance. An elevated cognitive load in interpreters may lead to the interpretation failures. The widely used NASA-TLX questionnaire effectively measures MWL. However, a global score was employed in previous interpretation studies, overlooking the distinct contributions of MWL components to the interpreters' performance. Accordingly, we recruited twenty novice interpreters who were postgraduate students specializing in interpreting to complete the consecutive interpreting task. Throughout the process, we used functional near-infrared spectroscopy (fNIRS) to monitor the hemodynamic response in participants' brains. The NASA-TLX was used to measure the MWL during interpreting with six components, including mental demand, physical demand, temporal demand, performance, effort, and frustration. Five interpretation experts were invited to assess the interpretation quality. The Bayes factor approach was employed to explore the components that contributes the most to the interpretation quality. It indicated that mental demand strongly contributed to the interpretation quality. Moreover, the mediation analysis revealed a positive correlation between mental demand and brain activation in three brain areas, which, in turn, was negatively correlated with interpretation quality, indicating the predictive role of mental demand in interpretation quality through the mediating of brain activation. The functions of the mediating brain areas, including the inferior frontal gyrus, middle temporal gyrus, and inferior temporal gyrus, aligned with the three efforts proposed by Gile's effort model, which emphasizes the significance of three fundamental efforts in achieving successful interpreting. These findings have implications for interpreter learning and training.

Informativeness across Interpreting Types: Implications for Language Shifts under Cognitive Load

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.

Differentiating Interpreting Types: Connecting Complex Networks to Cognitive Complexity

Prominent interpreting models have illustrated different processing mechanisms of simultaneous interpreting and consecutive interpreting. Although great efforts have been made, a macroscopic examination into interpreting outputs is sparse. Since complex network is a powerful and feasible tool to capture the holistic features of language, the present study adopts this novel approach to investigate different properties of syntactic dependency networks based on simultaneous interpreting and consecutive interpreting outputs. Our results show that consecutive interpreting networks demonstrate higher degrees, higher clustering coefficients, and a more important role of function words among the central vertices than simultaneous interpreting networks. These findings suggest a better connectivity, better transitivity, and a lower degree of vocabulary richness in consecutive interpreting outputs. Our research provides an integrative framework for the understanding of underlying mechanisms in diverse interpreting types.

Quantifying Interpreting Types: Language Sequence Mirrors Cognitive Load Minimization in Interpreting Tasks

Most interpreting theories claim that different interpreting types should involve varied processing mechanisms and procedures. However, few studies have examined their underlying differences. Even though some previous results based on quantitative approaches show that different interpreting types yield outputs of varying lexical and syntactic features, the grammatical parsing approach is limited. Language sequences that form without relying on parsing or processing with a specific linguistic approach or grammar excel other quantitative approaches at revealing the sequential behavior of language production. As a non-grammatically-bound unit of language sequences, frequency motif can visualize the local distribution of content and function words, and can also statistically classify languages and identify text types. Thus, the current research investigates the distribution, length and position-dependent properties of frequency motifs across different interpreting outputs in pursuit of the sequential generation behaviors. It is found that the distribution, the length and certain position-dependent properties of the specific language sequences differ significantly across simultaneous interpreting and consecutive interpreting output. The features of frequency motifs manifest that both interpreting output is produced in the manner that abides by the least effort principle. The current research suggests that interpreting types can be differentiated through this type of language sequential unit and offers evidence for how the different task features mediate the sequential organization of interpreting output under different demand to achieve cognitive load minimization.

Predicting Fluency With Language Proficiency, Working Memory, and Directionality in Simultaneous Interpreting

Simultaneous interpreting (SI) is a complex bilingual verbal activity that poses great challenges for working memory (WM) and language proficiency. Fluency is one of the crucial indicators in evaluating SI quality, the violation of which is characterized by disfluency indicators such as interruptions, hesitations, repetitions, corrections, and blanks. To uncover factors underlying fluency in SI, 22 interpreting students performed a battery of tasks to test their language proficiency and WM. Two SI tasks, both from Chinese to English and from English to Chinese, were also conducted, and fluency was evaluated according to the five indicators. Two factors (language proficiency and WM) and the five objectively measured disfluency indicators were then used as input for a regression analysis in both directions to model factors underlying fluency in SI performance. The results reveal that, with fluency measured as a whole, WM and directionality yield a significant effect on fluency, and that WM is the only variable that predicts fluency in both directions, accounting for 50 and 51% of the variation in the occurrence of disfluencies in Chinese-English and English-Chinese interpreting, respectively. The findings clarify for the first time the role of language proficiency, WM, and directionality upon fluency in SI, indicating the critical role of WM capability as compared with language skills in fluent production. The research also supports the position that, for interpreting students, interpreting performance tends to be more fluent in the non-native to native language direction.