Search Constraints
Number of results to display per page
Results for:
Language
English
Remove constraint Language: English
Resource Type
Video
Remove constraint Resource Type: Video
Year
2023
Remove constraint Year: 2023
1 - 2 of 2
Search Results
-
Video
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.
Event date: 4/12/2023
Speaker: Prof. Yanping Dong (Zhejiang University)
Hosted by: Faculty of Humanities
- Subjects:
- Translating and Interpreting and Language and Languages
- Keywords:
- Cognition Language languages Translating interpreting
- Resource Type:
- Video
-
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:
- Computational linguistics Language acquisition Machine learning
- Resource Type:
- Video