Exploring the Design Space for Human-Food-Technology Interaction: An Approach from the Lens of Eating Experiences

Embedded in everyday practices, food can be a rich resource for interaction design. This article focuses on eating experiences to uncover how bodily, sensory, and socio-cultural aspects of eating can be better leveraged for the design of user experience. We report a systematic literature review of 109 papers, and interviews with 18 professional chefs, providing new understandings of prior HFI research, as well as how professional chefs creatively design eating experiences. The findings inform a conceptual framework of designing for user experience leveraging eating experiences. These findings also inform implications for HFI design suggesting the value of multisensory flavor experiences, external and internal sensory stimulation and deprivation, aspects of eating for communicating meaning, and designing with contrasting pleasurable and uncomfortable experiences. The article concludes with six charts as novel generative design tools for HFI experiences focused on sensory, emotional, communicative, performative, and temporal experiences.

Chatbots Language Design: The Influence of Language Variation on User Experience with Tourist Assistant Chatbots

Chatbots are often designed to mimic social roles attributed to humans. However, little is known about the impact of using language that fails to conform to the associated social role. Our research draws on sociolinguistic to investigate how a chatbot’s language choices can adhere to the expected social role the agent performs within a context. We seek to understand whether chatbots design should account for linguistic register. This research analyzes how register differences play a role in shaping the user’s perception of the human-chatbot interaction. We produced parallel corpora of conversations in the tourism domain with similar content and varying register characteristics and evaluated users’ preferences of chatbot’s linguistic choices in terms of appropriateness, credibility, and user experience. Our results show that register characteristics are strong predictors of user’s preferences, which points to the needs of designing chatbots with register-appropriate language to improve acceptance and users’ perceptions of chatbot interactions.

Visual Communication Design Based on Collaborative Wireless Communication Video Transmission

With the development of wireless communication technology, video and multimedia have become an integral part of visual communication design. Designers want higher interactivity, diversity, humanization, and plurality of attributes in the process of visual communication. This makes the process of visual communication have high requirements for the quality and real-time data transmission. To address the problem of transmitting HD video in a heterogeneous wireless network with multiple concurrent streams to improve the transmission rate and thus enhance the user experience, with the optimization goal of minimizing the system transmission delay and the delay difference between paths, the video sender and receiver are jointly considered, and the video transmission rate and the cache size at the receiver are adaptively adjusted to improve the user experience, and a cooperative wireless communication video transmission based on the control model for video transmission based on cooperative wireless communication is established, and video streams with self-similarity and long correlation are studied based on Pareto distribution and P / P / l queuing theory, based on which an adaptive streaming decision method for video streams in heterogeneous wireless networks is proposed. Simulation results show that the proposed multistream concurrent adaptive transmission control method for heterogeneous networks is superior in terms of delay and packet loss rate compared with the general load balancing streaming decision method, in terms of transmission efficiency and accuracy.

Bilateral Personalized Dialogue Generation with Contrastive Learning

Generating personalized responses is one of the major challenges in natural human-robot interaction. Current researches in this field mainly focus on generating responses consistent with the robot’s pre-assigned persona, while ignoring the user’s persona. Such responses may be inappropriate or even offensive, which may lead to the bad user experience. Therefore, we propose a Bilateral Personalized Dialogue Generation (BPDG) method for dyadic conversation, which integrates user and robot personas into dialogue generation via designing a dynamic persona-aware fusion method. To bridge the gap between the learning objective function and evaluation metrics, the Conditional Mutual Information Maximum (CMIM) criterion is adopted with contrastive learning to select the proper response from the generated candidates. Moreover, a bilateral persona accuracy metric is designed to measure the degree of bilateral personalization. Experimental results demonstrate that, compared with several state-of-the-art methods, the final results of the proposed method are more personalized and consistent with bilateral personas in terms of both automatic and manual evaluations.

Multimodality in VR: A survey

Virtual reality (VR) is rapidly growing, with the potential to change the way we create and consume content. In VR, users integrate multimodal sensory information they receive, to create a unified perception of the virtual world. In this survey, we review the body of work addressing multimodality in VR, and its role and benefits in user experience, together with different applications that leverage multimodality in many disciplines. These works thus encompass several fields of research, and demonstrate that multimodality plays a fundamental role in VR; enhancing the experience, improving overall performance, and yielding unprecedented abilities in skill and knowledge transfer.

Extending Design Thinking, Content Strategy, and Artificial Intelligence into Technical Communication and User Experience Design Programs: Further Pedagogical Implications

This article follows up on the conversation about new streams of approaches in technical communication and user experience (UX) design, i.e., design thinking, content strategy, and artificial intelligence (AI), which afford implications for professional practice. By extending such implications to technical communication pedagogy, we aim to demonstrate the importance of paying attention to these streams in our programmatic development and provide strategies for doing so.