2020
DOI: 10.3389/fpsyg.2020.01864
|View full text |Cite
|
Sign up to set email alerts
|

The Predicting Power of Cognitive Fluency for the Development of Utterance Fluency in Simultaneous Interpreting

Abstract: Although simultaneous interpreting (SI) is generally recognized as a highly demanding cognitive activity in nature, the role of cognitive processes in SI fluency is yet to be determined. While utterance fluency refers to the set of objectively determined oral features of utterances, cognitive fluency means the speaker’s efficient mobilization and integration of underlying cognitive processes responsible for utterance production. An investigation into the relationship of the two dimensions of fluency helps to r… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

0
7
0

Year Published

2022
2022
2024
2024

Publication Types

Select...
7

Relationship

0
7

Authors

Journals

citations
Cited by 7 publications
(7 citation statements)
references
References 61 publications
(81 reference statements)
0
7
0
Order By: Relevance
“…Numerous factors may contribute to cognitive load during language production (for examples and overviews addressing different factors influencing cognitive load see Barkaoui 2019;Bourdin and Fayol 1994;Feng and Guo 2022;Johansson 2009;Kellogg 2008;Kellogg et al 2016;Lively et al 1993;Lourdes Ortega 2009;Manchón 2020;Song and Li 2020). Existing research in this area suggests that writers' and speakers' linguistic proficiency (including factors such as producing in one's first or second/third language, as well as overall grammatical and lexical knowledge), age, and education will influence fluency during language production.…”
Section: Language Production and Cognitive Loadmentioning
confidence: 99%
“…Numerous factors may contribute to cognitive load during language production (for examples and overviews addressing different factors influencing cognitive load see Barkaoui 2019;Bourdin and Fayol 1994;Feng and Guo 2022;Johansson 2009;Kellogg 2008;Kellogg et al 2016;Lively et al 1993;Lourdes Ortega 2009;Manchón 2020;Song and Li 2020). Existing research in this area suggests that writers' and speakers' linguistic proficiency (including factors such as producing in one's first or second/third language, as well as overall grammatical and lexical knowledge), age, and education will influence fluency during language production.…”
Section: Language Production and Cognitive Loadmentioning
confidence: 99%
“…In interpreting studies, disfluencies reflect the difficulty of the source text, such as syntactic complexity (Shen et al, 2023), dependency distance (Jiang, 2020), informational load (Kajzer-Wietrzny, 2023), or lexical density. In fact, disfluencies such as hesitations (including lengthening of vowels and filled pauses), silent pauses with extend of more than 0.3 second and interruptions of expressions (including repetitions, false starts and self-correction) have been considered as indicators of cognitive load during interpreting tasks in previous studies (Mead, 2000;Skehan, 2003;Song, 2020), as they occur when the interpreter processes complex or unfamiliar information and needs more time or attention to produce a coherent output (Jiang & Jiang, 2020;Plevoets & Defrancq, 2016). In addition, disfluencies (especially silent pauses) may indicate the cognitive strategies that interpreters use to cope with high load, such as simplification, segmentation, anticipation, or monitoring (Zhao, 2022).…”
Section: Silent Pauses As Indicator Of Cognitive Fluency In Simentioning
confidence: 99%
“…Fu (2013) and Yuan and Wan (2019) examined the impact of directionality on student interpreters' fluency in consecutive and sight interpreting tasks respectively, and found that directionality significantly correlates with fluency performance. Jiang and Jiang (2019) and Song et al (2021) invited student interpreters to finish sight interpreting and simultaneous interpreting tasks respectively, and concluded that maximum dependency distance and input rate have a significant impact on fluency performance. Tang (2020) proposed a framework of categorizing student interpreters' self-repairs in consecutive interpreting.…”
Section: Non-fluency In Interpretingmentioning
confidence: 99%