Yu-An Ko


2021

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Discussion on the relationship between elders’ daily conversations and cognitive executive function: using word vectors and regression models
Ming-Hsiang Su | Yu-An Ko | Man-Ying Wang
Proceedings of the 33rd Conference on Computational Linguistics and Speech Processing (ROCLING 2021)

As the average life expectancy of Chinese people rises, the health care problems of the elderly are becoming more diverse, and the demand for long-term care is also increasing. Therefore, how to help the elderly have a good quality of life and maintain their dignity is what we need to think about. This research intends to explore the characteristics of natural language of normal aging people through a deep model. First, we collect information through focus groups so that the elders can naturally interact with other participants in the process. Then, through the word vector model and regression model, an executive function prediction model based on dialogue data is established to help understand the degradation trajectory of executive function and establish an early warning.

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Predicting elders’ cognitive flexibility from their language use
Man-Ying Wang | Yu-An Ko | Chin-Lan Huang | Jyun-Hong Chen | Te-Tien Ting
Proceedings of the 33rd Conference on Computational Linguistics and Speech Processing (ROCLING 2021)

This study recruited 51 elders aged 53-74 to discuss their daily activities in focus groups. The transcribed discourse was analyzed using the Chinese version of LIWC (Lin et al., 2020; Pennebaker et al., 2015) for cognitive complexity and dynamic language as well as content words related to elders’ daily activities. The interruption behavior during the conversation was also coded and analyzed. After controlling for education, gender and age, the results showed that cognitive flexibility performance was accompanied by the increasing adoption of dynamic language, insight words and family words. These findings serve as the basis for predicting elders’ cognitive flexibility through their daily language use.