Target-text syntactic complexity as a predictor of disfluency in student consecutive interpreting

Abstract

Fluency management is a persistent challenge in interpreter training, particularly when students work into a B language. This study investigates how syntactic complexity in the target text (TT) affects disfluency in Korean-to-English consecutive interpreting by student interpreters. While previous research has examined cognitive load and general fluency, few studies have explored TT sentence complexity as a predictor of disfluency patterns. Drawing on data from six student interpreters, this study analyses disfluency frequency and type across sentences classified by Mean Dependency Distance (MDD). The findings show that TT syntactic complexity is positively associated with overall disfluency, with silent pauses most consistently affected, followed by fillers and self-repairs, while repetitions showed no reliable pattern. This relationship was confirmed through both linear and non-parametric analyses, revealing how specific disfluency types reflect structural processing strain. By focusing on a typologically distant language pair and analysing disfluency at the sentence level, the study adds empirical depth to fluency research in interpreting. It also offers pedagogical implications for helping trainees manage TT complexity more strategically during B language production.