Tootfinder

Introduction to Human-Robot Interaction: A Multi-Perspective Introductory Course
Tom Williams
https://arxiv.org/abs/2403.15323 https://

Introduction to Human-Robot Interaction: A Multi-Perspective Introductory Course
In this paper I describe the design of an introductory course in Human-Robot Interaction. This project-driven course is designed to introduce undergraduate and graduate engineering students, especially those enrolled in Computer Science, Mechanical Engineering, and Robotics degree programs, to key theories and methods used in the field of Human-Robot Interaction that they would otherwise be unlikely to see in those degree programs. To achieve this aim, the course takes students all the way from…

This https://arxiv.org/abs/2403.11384 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csHC_…

A Systematic Review of XR-based Remote Human-Robot Interaction Systems
This survey provides an exhaustive review of the applications of extended reality (XR) technologies in the field of remote human-computer interaction (HRI). We developed a systematic search strategy based on the PRISMA methodology. From the initial 2,561 articles selected, 100 research papers that met our inclusion criteria were included. We categorized and summarized the domain in detail, delving into XR technologies, including augmented reality (AR), virtual reality (VR), and mixed reality (M…

This https://arxiv.org/abs/2403.11384 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csHC_…

A Systematic Review of XR-based Remote Human-Robot Interaction Systems
This survey provides an exhaustive review of the applications of extended reality (XR) technologies in the field of remote human-computer interaction (HRI). We developed a systematic search strategy based on the PRISMA methodology. From the initial 2,561 articles selected, 100 research papers that met our inclusion criteria were included. We categorized and summarized the domain in detail, delving into XR technologies, including augmented reality (AR), virtual reality (VR), and mixed reality (M…

Deep functional multiple index models with an application to SER
Matthieu Saumard, Abir El Haj, Thibault Napoleon
https://arxiv.org/abs/2403.17562 https://…

Deep functional multiple index models with an application to SER
Speech Emotion Recognition (SER) plays a crucial role in advancing human-computer interaction and speech processing capabilities. We introduce a novel deep-learning architecture designed specifically for the functional data model known as the multiple-index functional model. Our key innovation lies in integrating adaptive basis layers and an automated data transformation search within the deep learning framework. Simulations for this new model show good performances. This allows us to extract f…

[2024-03-26 Tue (UTC), 20 new articles found for cs.HC Human-Computer Interaction]

Playing With Neuroscience: Past, Present and Future of Neuroimaging and Games
Paolo Burelli, Laurits Dixen
https://arxiv.org/abs/2403.15413 https://…

Playing With Neuroscience: Past, Present and Future of Neuroimaging and Games
Videogames have been a catalyst for advances in many research fields, such as artificial intelligence, human-computer interaction or virtual reality. Over the years, research in fields such as artificial intelligence has enabled the design of new types of games, while games have often served as a powerful tool for testing and simulation. Can this also happen with neuroscience? What is the current relationship between neuroscience and games research? what can we expect from the future? In this a…

This https://arxiv.org/abs/2402.13018 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

EMO-SUPERB: An In-depth Look at Speech Emotion Recognition
Speech emotion recognition (SER) is a pivotal technology for human-computer interaction systems. However, 80.77% of SER papers yield results that cannot be reproduced. We develop EMO-SUPERB, short for EMOtion Speech Universal PERformance Benchmark, which aims to enhance open-source initiatives for SER. EMO-SUPERB includes a user-friendly codebase to leverage 15 state-of-the-art speech self-supervised learning models (SSLMs) for exhaustive evaluation across six open-source SER datasets. EMO-SUPE…

Deep functional multiple index models with an application to SER
Matthieu Saumard, Abir El Haj, Thibault Napoleon
https://arxiv.org/abs/2403.17562 https://…

Deep functional multiple index models with an application to SER
Speech Emotion Recognition (SER) plays a crucial role in advancing human-computer interaction and speech processing capabilities. We introduce a novel deep-learning architecture designed specifically for the functional data model known as the multiple-index functional model. Our key innovation lies in integrating adaptive basis layers and an automated data transformation search within the deep learning framework. Simulations for this new model show good performances. This allows us to extract f…

[2024-03-27 Wed (UTC), 12 new articles found for cs.HC Human-Computer Interaction]

Maia: A Real-time Non-Verbal Chat for Human-AI Interaction
Dragos Costea, Alina Marcu, Cristina Lazar, Marius Leordeanu
https://arxiv.org/abs/2402.06385 ht…

Maia: A Real-time Non-Verbal Chat for Human-AI Interaction
Face-to-face communication modeling in computer vision is an area of research focusing on developing algorithms that can recognize and analyze non-verbal cues and behaviors during face-to-face interactions. We propose an alternative to text chats for Human-AI interaction, based on non-verbal visual communication only, using facial expressions and head movements that mirror, but also improvise over the human user, to efficiently engage with the users, and capture their attention in a low-cost an…

Today is the last day to register at the early bird rate to #CHI2024. I just did, because I am deadline-driven like nobody's business.
While you're at it, why not sign up for our CHI Course "Human-Computer Interaction and AI: What Practitioners Need to Know to Design and Build Effective AI systems from a Human Perspective"?
We'll have fun, I promise!

Playing With Neuroscience: Past, Present and Future of Neuroimaging and Games
Paolo Burelli, Laurits Dixen
https://arxiv.org/abs/2403.15413 https://…

Playing With Neuroscience: Past, Present and Future of Neuroimaging and Games
Videogames have been a catalyst for advances in many research fields, such as artificial intelligence, human-computer interaction or virtual reality. Over the years, research in fields such as artificial intelligence has enabled the design of new types of games, while games have often served as a powerful tool for testing and simulation. Can this also happen with neuroscience? What is the current relationship between neuroscience and games research? what can we expect from the future? In this a…

Looking for the Human in HRI Teaching: User-Centered Course Design for Tech-Savvy Students
Tobias Doernbach
https://arxiv.org/abs/2403.12607 https://

Looking for the Human in HRI Teaching: User-Centered Course Design for Tech-Savvy Students
Top-down, user-centered thinking is not typically a strength of all students, especially tech-savvy computer science-related ones. We propose Human-Robot Interaction (HRI) introductory courses as a highly suitable opportunity to foster these important skills since the HRI discipline includes a focus on humans as users. Our HRI course therefore contains elements like scenario-based design of laboratory projects, discussing and merging ideas and other self-empowerment techniques. Participants des…

sEMG-based Fine-grained Gesture Recognition via Improved LightGBM Model
Xiupeng Qiao, Zekun Chen, Shili Liang
https://arxiv.org/abs/2404.11861 https://

sEMG-based Fine-grained Gesture Recognition via Improved LightGBM Model
Surface electromyogram (sEMG), as a bioelectrical signal reflecting the activity of human muscles, has a wide range of applications in the control of prosthetics, human-computer interaction and so on. However, the existing recognition methods are all discrete actions, that is, every time an action is executed, it is necessary to restore the resting state before the next action, and it is unable to effectively recognize the gestures of continuous actions. To solve this problem, this paper propos…

[2024-03-25 Mon (UTC), 3 new articles found for cs.HC Human-Computer Interaction]

This was fun---a chat with the student newspaper: https://www.thecrimson.com/article/2024/3/29/elena-glassman-15q/

Fifteen Questions: Elena Glassman on Human-Computer Interaction, Freestyle Wrestling, and MIT Dorms | Magazine | The Harvard Crimson
The human-computer interaction expert sat down with FM to discuss software design, the importance of bicycling infrastructure, and her time competing in women’s freestyle wrestling.

[2024-04-24 Wed (UTC), 20 new articles found for cs.HC Human-Computer Interaction]

Artificial Neural Networks to Recognize Speakers Division from Continuous Bengali Speech
Hasmot Ali, Md. Fahad Hossain, Md. Mehedi Hasan, Sheikh Abujar, Sheak Rashed Haider Noori
https://arxiv.org/abs/2404.15168

Artificial Neural Networks to Recognize Speakers Division from Continuous Bengali Speech
Voice based applications are ruling over the era of automation because speech has a lot of factors that determine a speakers information as well as speech. Modern Automatic Speech Recognition (ASR) is a blessing in the field of Human-Computer Interaction (HCI) for efficient communication among humans and devices using Artificial Intelligence technology. Speech is one of the easiest mediums of communication because it has a lot of identical features for different speakers. Nowadays it is possibl…

Synthesizing Sentiment-Controlled Feedback For Multimodal Text and Image Data
Puneet Kumar, Sarthak Malik, Balasubramanian Raman, Xiaobai Li
https://arxiv.org/abs/2402.07640

Synthesizing Sentiment-Controlled Feedback For Multimodal Text and Image Data
The ability to generate sentiment-controlled feedback in response to multimodal inputs, comprising both text and images, addresses a critical gap in human-computer interaction by enabling systems to provide empathetic, accurate, and engaging responses. This capability has profound applications in healthcare, marketing, and education. To this end, we construct a large-scale Controllable Multimodal Feedback Synthesis (CMFeed) dataset and propose a controllable feedback synthesis system. The propo…

A Systematic Review of XR-based Remote Human-Robot Interaction Systems
Xian Wang, Luyao Shen, Lik-Hang Lee
https://arxiv.org/abs/2403.11384 https://…

A Systematic Review of XR-based Remote Human-Robot Interaction Systems
This survey provides an exhaustive review of the applications of extended reality (XR) technologies in the field of remote human-computer interaction (HRI). We developed a systematic search strategy based on the PRISMA methodology. From the initial 2,561 articles selected, 100 research papers that met our inclusion criteria were included. We categorized and summarized the domain in detail, delving into XR technologies, including augmented reality (AR), virtual reality (VR), and mixed reality (M…

Dynamic Resolution Guidance for Facial Expression Recognition
Jie Ou, Xu Li, Tianxiang Jiang, Yuanlun Xie
https://arxiv.org/abs/2404.06365 https://<…

Dynamic Resolution Guidance for Facial Expression Recognition
Facial expression recognition (FER) is vital for human-computer interaction and emotion analysis, yet recognizing expressions in low-resolution images remains challenging. This paper introduces a practical method called Dynamic Resolution Guidance for Facial Expression Recognition (DRGFER) to effectively recognize facial expressions in images with varying resolutions without compromising FER model accuracy. Our framework comprises two main components: the Resolution Recognition Network (RRN) an…

A Systematic Review of XR-based Remote Human-Robot Interaction Systems
Xian Wang, Luyao Shen, Lik-Hang Lee
https://arxiv.org/abs/2403.11384 https://…

A Systematic Review of XR-based Remote Human-Robot Interaction Systems
This survey provides an exhaustive review of the applications of extended reality (XR) technologies in the field of remote human-computer interaction (HRI). We developed a systematic search strategy based on the PRISMA methodology. From the initial 2,561 articles selected, 100 research papers that met our inclusion criteria were included. We categorized and summarized the domain in detail, delving into XR technologies, including augmented reality (AR), virtual reality (VR), and mixed reality (M…

This https://arxiv.org/abs/2403.06998 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

High-speed Low-consumption sEMG-based Transient-state micro-Gesture Recognition by Spiking Neural Network
Gesture recognition on wearable devices is extensively applied in human-computer interaction. Electromyography (EMG) has been used in many gesture recognition systems for its rapid perception of muscle signals. However, analyzing EMG signals on devices, like smart wristbands, usually needs inference models to have high performances, such as low inference latency, low power consumption, and low memory occupation. Therefore, this paper proposes an improved spiking neural network (SNN) to achieve …

A critical analysis of cognitive load measurement methods for evaluating the usability of different types of interfaces: guidelines and framework for Human-Computer Interaction
Ali Darejeh, Nadine Marcusa, Gelareh Mohammadi, John Sweller
https://arxiv.org/abs/2402.11820

A critical analysis of cognitive load measurement methods for evaluating the usability of different types of interfaces: guidelines and framework for Human-Computer Interaction
Usability testing is an essential part of product design, particularly for user interfaces. To enhance the reliability of usability evaluations, employing cognitive load measurement methods can be highly effective in assessing the mental effort required to complete tasks during user testing. This review aims to provide an overview of the most suitable cognitive load measurement methods for evaluating various types of user interfaces, serving as a valuable resource for guiding usability assessme…

[2024-02-23 Fri (UTC), 12 new articles found for cs.HC Human-Computer Interaction]

This https://arxiv.org/abs/2403.01766 has been replaced.
link: https://scholar.google.com/scholar?q=a

Improving Visual Perception of a Social Robot for Controlled and In-the-wild Human-robot Interaction
Social robots often rely on visual perception to understand their users and the environment. Recent advancements in data-driven approaches for computer vision have demonstrated great potentials for applying deep-learning models to enhance a social robot's visual perception. However, the high computational demands of deep-learning methods, as opposed to the more resource-efficient shallow-learning models, bring up important questions regarding their effects on real-world interaction and user exp…

This https://arxiv.org/abs/2403.06998 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

High-speed Low-consumption sEMG-based Transient-state micro-Gesture Recognition by Spiking Neural Network
Gesture recognition on wearable devices is extensively applied in human-computer interaction. Electromyography (EMG) has been used in many gesture recognition systems for its rapid perception of muscle signals. However, analyzing EMG signals on devices, like smart wristbands, usually needs inference models to have high performances, such as low inference latency, low power consumption, and low memory occupation. Therefore, this paper proposes an improved spiking neural network (SNN) to achieve …

[2024-04-22 Mon (UTC), 14 new articles found for cs.HC Human-Computer Interaction]

EMO-SUPERB: An In-depth Look at Speech Emotion Recognition
Haibin Wu, Huang-Cheng Chou, Kai-Wei Chang, Lucas Goncalves, Jiawei Du, Jyh-Shing Roger Jang, Chi-Chun Lee, Hung-Yi Lee
https://arxiv.org/abs/2402.13018

EMO-SUPERB: An In-depth Look at Speech Emotion Recognition
Speech emotion recognition (SER) is a pivotal technology for human-computer interaction systems. However, 80.77% of SER papers yield results that cannot be reproduced. We develop EMO-SUPERB, short for EMOtion Speech Universal PERformance Benchmark, which aims to enhance open-source initiatives for SER. EMO-SUPERB includes a user-friendly codebase to leverage 15 state-of-the-art speech self-supervised learning models (SSLMs) for exhaustive evaluation across six open-source SER datasets. EMO-SUPE…

This https://arxiv.org/abs/2312.15583 has been replaced.
link: https://scholar.google.com/scholar?q=a

ITEACNet: Inverted Teacher-studEnt seArch Conversation Network
Due to the widespread applications of conversations in human-computer interaction, Conversation Emotion Recognition (CER) has attracted increasing attention from researchers. In real-world scenarios, the emotional states of both participants in a conversation tend to maintain a relatively stable pattern within the local context, and often encountering issues with incomplete data patterns. Focusing on these two key challenges, we propose a novel framework for incomplete multimodal learning in CE…

[2024-03-22 Fri (UTC), 12 new articles found for cs.HC Human-Computer Interaction]

[2024-02-22 Thu (UTC), 7 new articles found for cs.HC Human-Computer Interaction]

High-speed Low-consumption sEMG-based Transient-state micro-Gesture Recognition by Spiking Neural Network
Youfang Han, Wei Zhao, Xiangjin Chen, Xin Meng
https://arxiv.org/abs/2403.06998

High-speed Low-consumption sEMG-based Transient-state micro-Gesture Recognition by Spiking Neural Network
Gesture recognition on wearable devices is extensively applied in human-computer interaction. Electromyography (EMG) has been used in many gesture recognition systems for its rapid perception of muscle signals. However, analyzing EMG signals on devices, like smart wristbands, usually needs inference models to have high performances, such as low inference latency, low power consumption, and low memory occupation. Therefore, this paper proposes an improved spiking neural network (SNN) to achieve …

Children Age Group Detection based on Human-Computer Interaction and Time Series Analysis
Juan Carlos Ruiz-Garcia, Carlos Hojas, Ruben Tolosana, Ruben Vera-Rodriguez, Aythami Morales, Julian Fierrez, Javier Ortega-Garcia, Jaime Herreros-Rodriguez
https://arxiv.org/abs/2403.04574

Children Age Group Detection based on Human-Computer Interaction and Time Series Analysis
This article proposes a novel Children-Computer Interaction (CCI) approach for the task of age group detection. This approach focuses on the automatic analysis of the time series generated from the interaction of the children with mobile devices. In particular, we extract a set of 25 time series related to spatial, pressure, and kinematic information of the children interaction while colouring a tree through a pen stylus tablet, a specific test from the large-scale public ChildCIdb database. …

[2024-03-21 Thu (UTC), 9 new articles found for cs.HC Human-Computer Interaction]

Ethical Concerns when Working with Mixed-Ability Groups of Children
Patricia Piedade, Ana Henriques, Filipa Rocha, Isabel Neto, Hugo Nicolau
https://arxiv.org/abs/2404.11248

Ethical Concerns when Working with Mixed-Ability Groups of Children
Accessibility research has gained traction, yet ethical gaps persist in the inclusion of individuals with disabilities, especially children. Inclusive research practices are essential to ensure research and design solutions cater to the needs of all individuals, regardless of their abilities. Working with children with disabilities in Human-Computer Interaction and Human-Robot Interaction presents a unique set of ethical dilemmas. These young participants often require additional care, support,…

[2024-03-20 Wed (UTC), 11 new articles found for cs.HC Human-Computer Interaction]

Cascaded Self-supervised Learning for Subject-independent EEG-based Emotion Recognition
Hanqi Wang, Tao Chen, Liang Song
https://arxiv.org/abs/2403.04041 h…

Cascaded Self-supervised Learning for Subject-independent EEG-based Emotion Recognition
EEG-based Emotion recognition holds significant promise for applications in human-computer interaction, medicine, and neuroscience. While deep learning has shown potential in this field, current approaches usually rely on large-scale high-quality labeled datasets, limiting the performance of deep learning. Self-supervised learning offers a solution by automatically generating labels, but its inter-subject generalizability remains under-explored. For this reason, our interest lies in offering a …

[2024-02-20 Tue (UTC), 13 new articles found for cs.HC Human-Computer Interaction]

Effect of external characteristics of a virtual human being during the use of a computer-assisted therapy tool
Navid Ashrafi, Vanessa Neuhaus, Francesco Vona, Nicolina Laura Peperkorn, Youssef Shiban, Jan-Niklas Voigt-Antons
https://arxiv.org/abs/2403.09544

Effect of external characteristics of a virtual human being during the use of a computer-assisted therapy tool
Identification within media, whether with real or fictional characters, significantly impacts users, shaping their behavior and enriching their social and emotional experiences. Immersive media, like video games, utilize virtual entities such as agents, avatars, or NPCs to connect users with virtual worlds, fostering a heightened sense of immersion and identification. However, challenges arise in visually representing these entities, with design decisions crucial for enhancing user interaction.…

[2024-04-19 Fri (UTC), 9 new articles found for cs.HC Human-Computer Interaction]

Advancing Social Intelligence in AI Agents: Technical Challenges and Open Questions
Leena Mathur, Paul Pu Liang, Louis-Philippe Morency
https://arxiv.org/abs/2404.11023

Advancing Social Intelligence in AI Agents: Technical Challenges and Open Questions
Building socially-intelligent AI agents (Social-AI) is a multidisciplinary, multimodal research goal that involves creating agents that can sense, perceive, reason about, learn from, and respond to affect, behavior, and cognition of other agents (human or artificial). Progress towards Social-AI has accelerated in the past decade across several computing communities, including natural language processing, machine learning, robotics, human-machine interaction, computer vision, and speech. Natural…

This https://arxiv.org/abs/2402.13018 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

EMO-SUPERB: An In-depth Look at Speech Emotion Recognition
Speech emotion recognition (SER) is a pivotal technology for human-computer interaction systems. However, 80.77% of SER papers yield results that cannot be reproduced. We develop EMO-SUPERB, short for EMOtion Speech Universal PERformance Benchmark, which aims to enhance open-source initiatives for SER. EMO-SUPERB includes a user-friendly codebase to leverage 15 state-of-the-art speech self-supervised learning models (SSLMs) for exhaustive evaluation across six open-source SER datasets. EMO-SUPE…

[2024-03-19 Tue (UTC), 16 new articles found for cs.HC Human-Computer Interaction]

[2024-03-19 Tue (UTC), 16 new articles found for cs.HC Human-Computer Interaction]

[2024-02-19 Mon (UTC), 7 new articles found for cs.HC Human-Computer Interaction]

[2024-04-18 Thu (UTC), 13 new articles found for cs.HC Human-Computer Interaction]

[2024-03-18 Mon (UTC), 11 new articles found for cs.HC Human-Computer Interaction]

This https://arxiv.org/abs/2402.13018 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

EMO-SUPERB: An In-depth Look at Speech Emotion Recognition
Speech emotion recognition (SER) is a pivotal technology for human-computer interaction systems. However, 80.77% of SER papers yield results that cannot be reproduced. We develop EMO-SUPERB, short for EMOtion Speech Universal PERformance Benchmark, which aims to enhance open-source initiatives for SER. EMO-SUPERB includes a user-friendly codebase to leverage 15 state-of-the-art speech self-supervised learning models (SSLMs) for exhaustive evaluation across six open-source SER datasets. EMO-SUPE…

Characterizing and modeling harms from interactions with design patterns in AI interfaces
Lujain Ibrahim, Luc Rocher, Ana Valdivia
https://arxiv.org/abs/2404.11370

Characterizing and modeling harms from interactions with design patterns in AI interfaces
The proliferation of applications using artificial intelligence (AI) systems has led to a growing number of users interacting with these systems through sophisticated interfaces. Human-computer interaction research has long shown that interfaces shape both user behavior and user perception of technical capabilities and risks. Yet, practitioners and researchers evaluating the social and ethical risks of AI systems tend to overlook the impact of anthropomorphic, deceptive, and immersive interface…

Love, Joy, and Autism Robots: A Metareview and Provocatype
Andrew Hundt, Gabrielle Ohlson, Pieter Wolfert, Lux Miranda, Sophia Zhu, Katie Winkle
https://arxiv.org/abs/2403.05098 <…

Love, Joy, and Autism Robots: A Metareview and Provocatype
Previous work has observed how Neurodivergence is often harmfully pathologized in Human-Computer Interaction (HCI) and Human-Robot interaction (HRI) research. We conduct a review of autism robot reviews and find the dominant research direction is Autistic people's second to lowest (24 of 25) research priority: interventions and treatments purporting to 'help' neurodivergent individuals to conform to neurotypical social norms, become better behaved, improve social and emotional skills, and other…

[2024-04-15 Mon (UTC), 5 new articles found for cs.HC Human-Computer Interaction]

[2024-02-16 Fri (UTC), 14 new articles found for cs.HC Human-Computer Interaction]

[2024-03-15 Fri (UTC), 28 new articles found for cs.HC Human-Computer Interaction]

GazePointAR: A Context-Aware Multimodal Voice Assistant for Pronoun Disambiguation in Wearable Augmented Reality
Jaewook Lee, Jun Wang, Elizabeth Brown, Liam Chu, Sebastian S. Rodriguez, Jon E. Froehlich
https://arxiv.org/abs/2404.08213

GazePointAR: A Context-Aware Multimodal Voice Assistant for Pronoun Disambiguation in Wearable Augmented Reality
Voice assistants (VAs) like Siri and Alexa are transforming human-computer interaction; however, they lack awareness of users' spatiotemporal context, resulting in limited performance and unnatural dialogue. We introduce GazePointAR, a fully-functional context-aware VA for wearable augmented reality that leverages eye gaze, pointing gestures, and conversation history to disambiguate speech queries. With GazePointAR, users can ask "what's over there?" or "how do I solve this math problem?" simpl…

Bridging the Gap: Advancements in Technology to Support Dementia Care -- A Scoping Review
Yong Ma, Oda Elise Nordberg, Jessica Hubbers, Yuchong Zhang, Arvid Rongve, Miroslav Bachinski, Morten Fjeld
https://arxiv.org/abs/2404.09685

Bridging the Gap: Advancements in Technology to Support Dementia Care -- A Scoping Review
Dementia has serious consequences for the daily life of the person affected due to the decline in the their cognitive, behavioral and functional abilities. Caring for people living with dementia can be challenging and distressing. Innovative solutions are becoming essential to enrich the lives of those impacted and alleviate caregiver burdens. This scoping review, spanning literature from 2010 to July 2023 in the field of Human-Computer Interaction (HCI), offers a comprehensive look at how inte…

[2024-02-15 Thu (UTC), 10 new articles found for cs.HC Human-Computer Interaction]

[2024-03-13 Wed (UTC), 9 new articles found for cs.HC Human-Computer Interaction]

[2024-04-12 Fri (UTC), 15 new articles found for cs.HC Human-Computer Interaction]

Vision-Based Hand Gesture Customization from a Single Demonstration
Soroush Shahi, Cori Tymoszek Park, Richard Kang, Asaf Liberman, Oron Levy, Jun Gong, Abdelkareem Bedri, Gierad Laput
https://arxiv.org/abs/2402.08420

Vision-Based Hand Gesture Customization from a Single Demonstration
Hand gesture recognition is becoming a more prevalent mode of human-computer interaction, especially as cameras proliferate across everyday devices. Despite continued progress in this field, gesture customization is often underexplored. Customization is crucial since it enables users to define and demonstrate gestures that are more natural, memorable, and accessible. However, customization requires efficient usage of user-provided data. We introduce a method that enables users to easily design …

[2024-02-13 Tue (UTC), 17 new articles found for cs.HC Human-Computer Interaction]

[2024-04-11 Thu (UTC), 10 new articles found for cs.HC Human-Computer Interaction]

[2024-03-11 Mon (UTC), 18 new articles found for cs.HC Human-Computer Interaction]

[2024-02-12 Mon (UTC), 9 new articles found for cs.HC Human-Computer Interaction]

Cymatics Cup: Shape-Changing Drinks by Leveraging Cymatics
Weijen Chen, Yang Yang, Kao-Hua Liu, Yun Suen Pai, Junichi Yamaoka, Kouta Minamizawa
https://arxiv.org/abs/2404.06027

Cymatics Cup: Shape-Changing Drinks by Leveraging Cymatics
To enhance the dining experience, prior studies in Human-Computer Interaction (HCI) and gastrophysics have demonstrated that modifying the static shape of solid foods can amplify taste perception. However, the exploration of dynamic shape-changing mechanisms in liquid foods remains largely untapped. In the present study, we employ cymatics, a scientific discipline focused on utilizing sound frequencies to generate patterns in liquids and particles to augment the drinking experience. Utilizing s…

[2024-04-08 Mon (UTC), 10 new articles found for cs.HC Human-Computer Interaction]

[2024-03-07 Thu (UTC), 8 new articles found for cs.HC Human-Computer Interaction]

[2024-03-06 Wed (UTC), 10 new articles found for cs.HC Human-Computer Interaction]

[2024-04-05 Fri (UTC), 10 new articles found for cs.HC Human-Computer Interaction]

[2024-04-05 Fri (UTC), 10 new articles found for cs.HC Human-Computer Interaction]

[2024-03-05 Tue (UTC), no new articles found for cs.HC Human-Computer Interaction]

"I'm categorizing LLM as a productivity tool": Examining ethics of LLM use in HCI research practices
Shivani Kapania, Ruiyi Wang, Toby Jia-Jun Li, Tianshi Li, Hong Shen
https://arxiv.org/abs/2403.19876

"I'm categorizing LLM as a productivity tool": Examining ethics of LLM use in HCI research practices
Large language models are increasingly applied in real-world scenarios, including research and education. These models, however, come with well-known ethical issues, which may manifest in unexpected ways in human-computer interaction research due to the extensive engagement with human subjects. This paper reports on research practices related to LLM use, drawing on 16 semi-structured interviews and a survey conducted with 50 HCI researchers. We discuss the ways in which LLMs are already being u…

[2024-04-04 Thu (UTC), 11 new articles found for cs.HC Human-Computer Interaction]

[2024-03-04 Mon (UTC), 15 new articles found for cs.HC Human-Computer Interaction]

[2024-04-02 Tue (UTC), no new articles found for cs.HC Human-Computer Interaction]

[2024-04-01 Mon (UTC), 2 new articles found for cs.HC Human-Computer Interaction]

[2024-02-29 Thu (UTC), 10 new articles found for cs.HC Human-Computer Interaction]

[2024-02-28 Wed (UTC), 8 new articles found for cs.HC Human-Computer Interaction]

[2024-02-01 Thu (UTC), no new articles found for cs.HC Human-Computer Interaction]

[2024-03-29 Fri (UTC), 8 new articles found for cs.HC Human-Computer Interaction]

[2024-01-31 Wed (UTC), 12 new articles found for cs.HC Human-Computer Interaction]

[2024-03-28 Thu (UTC), 8 new articles found for cs.HC Human-Computer Interaction]

[2024-01-29 Mon (UTC), 15 new articles found for cs.HC Human-Computer Interaction]

LLMs in HCI Data Work: Bridging the Gap Between Information Retrieval and Responsible Research Practices
Neda Taghizadeh Serajeh, Iman Mohammadi, Vittorio Fuccella, Mattia De Rosa
https://arxiv.org/abs/2403.18173

LLMs in HCI Data Work: Bridging the Gap Between Information Retrieval and Responsible Research Practices
Efficient and accurate information extraction from scientific papers is significant in the rapidly developing human-computer interaction research in the literature review process. Our paper introduces and analyses a new information retrieval system using state-of-the-art Large Language Models (LLMs) in combination with structured text analysis techniques to extract experimental data from HCI literature, emphasizing key elements. Then We analyze the challenges and risks of using LLMs in the worl…