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The relationship between language experience and cognitive control (e.g., working memory, inhibitory control, cognitive flexibility) could be very well illustrated by the cognitively demanding language experience of interpreting training. A series of our empirical studies with interpreting students (see DONG 2023 for a review), together with studies with professional interpreters in the literature, suggest that interpreting training may first enhance students’ working memory (WM) updating ability and then WM spans, with probable some decline of WM updating ability between the shift from the two WM abilities. Similar patterns may appear in other cognitive control functions, such as cognitive flexibility (first with switching cost reduced and then with mixing cost reduced) and multi-tasking coordination. These results could be explained by the task features of interpreting (including task schemas and their cognitive loads) (see DONG & LI 2020), suggesting a close and dynamic relationship between language experience and cognitive control.
Even date: 4/12/2023
Speaker: Prof. Yanping Dong (Zhejiang University)
Hosted by: Faculty of Humanities
- Subjects:
- Language and Languages and Translating and Interpreting
- Keywords:
- Translating interpreting Language languages Cognition
- Resource Type:
- Video
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Video
我們的日常生活每時每刻都離不開語言，每一個人都會對語言中發生的問題感興趣，但是卻並不知道這些生活中的語言問題有沒有學術研究價值。本講座將以日常生活中的語言現象為例，重點介紹語言研究的選題、研究方法和研究路徑，以期對研究生的選題和論文寫作以及語言的跨學科研究有所啟發。
日期：2023年9月15日
講者：崔希亮教授
主辦：人文學院
- Subjects:
- Language and Languages
- Keywords:
- Sociolinguistics
- Resource Type:
- Video
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Video
Psychology, Computer Science and Neuroscience have a history of shared questions and inter-related advances. Recently, new technology has enabled those fields to move from “toy” small-scale approaches to the study of language learning from raw sensory input and to do so at a large scale that constitutes daily life. The three primary goals of my research are 1) to quantify the statistical regularities in the real world, 2) to examine the underlying computational mechanisms operated on the statistical data, and 3) to apply the findings from basic science to real-world applications. In this talk, I will present several projects in my research lab to show that the advances in human learning and machine learning fields place us at the tipping point for powerful and consequential new insights into mechanisms of (and algorithms for) learning.
Event Date: 28/06/2023
Speaker: Prof. Chen YU (University of Texas at Austin)
Hosted by: Faculty of Humanities
- Subjects:
- Language and Languages
- Keywords:
- Machine learning Language acquisition Computational linguistics
- Resource Type:
- Video