An Empathy-Based Sandbox Approach to Bridge Attitudes, Goals, Knowledge, and Behaviors in the Privacy Paradox

Chaoran Chen, Weijun Li, Wenxin Song, Yanfang Ye, Yaxing Yao, Toby Jia-jun Li

CHI 2024 We introduce an empathy-based approach that allows users to experience how privacy behaviors may alter system outcomes in a risk-free sandbox environment from the perspective of artificially generated personas. To generate realistic personas, we introduce a novel pipeline that augments the outputs of large language models using few-shot learning, contextualization, and chain of thoughts.

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Practices and Challenges of Delivering Among Deaf or Hard of Hearing Couriers

Shi Chen, Xiaodong Wang, Weijun Li, Jiangao Zhang, Yuge Qi, Jiaqi Teng, Zhihan Zeng

CHI 2024 This paper explores the experiences of Deaf and Hard of Hearing (DHH) food delivery workers in China. We focus on their motivations, like better pay and community belonging, and their use of delivery platform tools, such as AI voice calls, for communication. Despite technological aids, human intervention remains important. We identify challenges such as safety risks, multitasking complexities, and mistrust in AI voice calls. Our findings offer insights for designing inclusive delivery platforms and broader implications for employment opportunities for DHH individuals, particularly in developing countries.

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What makes virtual intimacy...intimate? Understanding the Phenomenon and Practice of Computer-Mediated Paid Companionship

Weijun Li, Shi Chen, Lingyun Sun, Changyuan Yang

CSCW 2023 In China, Virtual romance service (VRS) provides a direct dyadic intimacy, different from fan-idol parasocial ties. Our study of 178 surveys and 22 interviews revealed virtual lovers' strategies to meet customers' emotional needs. Customers value VRS for its emotional benefits without the need for long-term commitment. We conclude with insights into the unique nature of virtual lovers and design implications for digital companionship.

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PTeacher, a Computer-Aided Personalized Pronunciation Training System with Exaggerated Audio-Visual Corrective Feedback

Yaohua Bu*, Tianyi Ma*, Weijun Li, Hang Zhou, Jia Jia, Kaiyuan Xu, Dachuan Shi, Haozhe Wu, Zhihan Yang, Kun Li, Zhiyong Wu, Yuanchun Shi, Xiaobo Lu, Ziwei Liu

CHI 2021 L2 English learners find it difficult to improve pronunciation due to lack of personalized feedback. This paper presents Pronunciation Teacher (PTeacher), a CAPT system offering personalized exaggerated audio-visual feedback. Interviewing 100 L2 learners and 22 native teachers, we propose three metrics to determine exaggeration levels in both modalities. We incorporate dynamic feedback based on learner proficiency. User studies indicate our system improves learning efficiency.

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I Never Envy Anyone, for I Have Already Built a Kingdom With My Fingertips, Exploring Teenagers’ Experience in Chat-based Cosplay Community

Weijun Li, Yaohua Bu, Suqi Lou, Shi Chen, Lingyun Sun, Changyuan Yang

IDC 23 This paper examines teenagers' chat-based cosplay in China. We found four primary motivations and their main practice. Adolescents perceived character presentation as key and devoted significant effort to refine their characters for higher consistency. We spotlight the interplay between social relationships and story creation, and also note both positive and negative experiences within the community.

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EdibleToy:Empowering Children to Create Their Own Meals with a DIY Wafer Paper Kit

Yilin Shao, Boyu Feng, Yingpin Chen, Yue Yang, Weijun Li, Yifan Yan, Yanan Wang, Ye Tao, Lingyun Sun, Guanyun Wang

IDC 23 Drawing inspiration from shape-changing food research, we propose an approach that combines deformable wafer paper for food preparation. We summarize the principles of wafer paper controllable deformation and develop a toolkit to facilitate its use. We support children increating personalized, transformable food items using this method.

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Visual-speech Synthesis of Exaggerated Corrective Feedback

Yaohua Bu*, Weijun Li*, Tianyi Ma, Shengqi Chen, Jia Jia, Kun Li, Xiaobo Lu

MM 2020 We propose a method for exaggerated visual-speech feedback in CAPT. The speech exaggeration is realized by an emphatic speech generation neural network based on Tacotron, while the visual exaggeration is accomplished by ADC Viseme Blending, namely increasing Amplitude of movement, extending the phone’s Duration and enhancing the color Contrast.

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An Integrated Method to Build Read-Aiding E-Books Based on Text Mining and Interactive Aesthetics

Weijun Li, Fukai Yang, Ruibing Jia, Renmin Li, Minghao Yin

JCDL 2020 We propose a four-stage method to build read-aiding e-books directly from text, integrating the technologies in text mining and the ideas in interactive aesthetics. By applying this method, we manage to identify and present multiple complex relationships in the classical Chinese novel Romance of the Three Kingdoms, providing readers with vivid scenes and rich interactions for better comprehension.

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