huashen218/convxai-cia-dataset huggingface dataset:
Title: Augmented Reality Glasses as an Orientation and Mobility Aid for People with Low Vision: a Feasibility Study of Experiences and Requirements
Authors: family: Min Htike
given: Hein; family: H. Margrain
given: Tom; family: Lai
given: Yu-Kun; family: Eslambolchilar
given: Parisa
Venue: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
Keywords: augmented reality, mobility aids, low vision, vision enhancement

Abstract: People with low vision experience reduced mobility that affects their physical and mental wellbeing. With augmented reality (AR) glasses, there are new opportunities to provide visual and auditory information that can improve mobility for this vulnerable group. Current research into AR-based mobility aids has focused mainly on the technical aspects, and less emphasis has been placed on understanding the usability and suitability of these aids in people with various levels of visual impairment. In this paper, we present the results of qualitative interviews with 18 participants using HoloLens v1 and eight prototype augmentations to understand how these enhancements are perceived by people with low vision and how these aids should be adjusted to suit their needs. Our results suggested that participants with moderate vision loss could potentially perceive the most benefit from glasses and underlined the importance of extensive customizability to accommodate the needs of a highly varied low vision population.
Title: Exploring Augmented Visual Alterations in Interpersonal Communication
Authors: family: Rixen
given: Jan Ole; family: Hirzle
given: Teresa; family: Colley
given: Mark; family: Etzel
given: Yannick; family: Rukzio
given: Enrico; family: Gugenheimer
given: Jan
Venue: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
Keywords: social acceptability, Augmented Reality, interpersonal communication, color-in-context, visual alterations

Abstract: Augmented Reality (AR) glasses equip users with the tools to modify the visual appearance of their surrounding environment. This might severely impact interpersonal communication, as the conversational partners will no longer share the same visual perception of reality. Grounded in color-in-context theory, we present a potential AR application scenario in which users can modify the color of the environment to achieve subconscious benefits. In a consecutive online survey (N=64), we measured the user’s comfort, acceptance of altering and being altered, and how it is impacted by being able to perceive or not perceive the alteration. We identified significant differences depending on (1) who or what is the target of the alteration, (2) which body part is altered, and (3) which relationship the conversational partners share. In light of our quantitative and qualitative findings, we discuss ethical and practical implications for future devices and applications that employ visual alterations.
Title: Crowdsourcing Design Guidance for Contextual Adaptation of Text Content in Augmented Reality
Authors: family: Dudley
given: John J.; family: Jacques
given: Jason T.; family: Kristensson
given: Per Ola
Venue: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
Keywords: Augmented Reality, Crowdsourcing, Privacy

Abstract: Augmented Reality (AR) can deliver engaging user experiences that seamlessly meld virtual content with the physical environment. However, building such experiences is challenging due to the developer’s inability to assess how uncontrolled deployment contexts may influence the user experience. To address this issue, we demonstrate a method for rapidly conducting AR experiments and real-world data collection in the user’s own physical environment using a privacy-conscious mobile web application. The approach leverages the large number of distinct user contexts accessible through crowdsourcing to efficiently source diverse context and perceptual preference data. The insights gathered through this method complement emerging design guidance and sample-limited lab-based studies. The utility of the method is illustrated by re-examining the design challenge of adapting AR text content to the user’s environment. Finally, we demonstrate how gathered design insight can be operationalized to provide adaptive text content functionality in an AR headset.
Title: The Impact of Multiple Parallel Phrase Suggestions on Email Input and Composition Behaviour of Native and Non-Native English Writers
Authors: family: Buschek
given: Daniel; family: Zürn
given: Martin; family: Eiband
given: Malin
Venue: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
Keywords: deep learning, Text entry, text suggestions, language model, dataset, typing, neural network

Abstract: We present an in-depth analysis of the impact of multi-word suggestion choices from a neural language model on user behaviour regarding input and text composition in email writing. Our study for the first time compares different numbers of parallel suggestions, and use by native and non-native English writers, to explore a trade-off of “efficiency vs ideation”, emerging from recent literature. We built a text editor prototype with a neural language model (GPT-2), refined in a prestudy with 30 people. In an online study (N=156), people composed emails in four conditions (0/1/3/6 parallel suggestions). Our results reveal (1) benefits for ideation, and costs for efficiency, when suggesting multiple phrases; (2) that non-native speakers benefit more from more suggestions; and (3) further insights into behaviour patterns. We discuss implications for research, the design of interactive suggestion systems, and the vision of supporting writers with AI instead of replacing them.
Title: Adaptive Subtitles: Preferences and Trade-Offs in Real-Time Media Adaption
Authors: family: Gorman
given: Benjamin M.; family: Crabb
given: Michael; family: Armstrong
given: Michael
Venue: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
Keywords: Captions, Adaptive-Interfaces, Media, Closed-captions, Subtitles

Abstract: Subtitles can help improve the understanding of media content. People enable subtitles based on individual characteristics (e.g., language or hearing ability), viewing environment, or media context (e.g., drama, quiz show). However, some people find that subtitles can be distracting and that they negatively impact their viewing experience. We explore the challenges and opportunities surrounding interaction with real-time personalisation of subtitled content. To understand how people currently interact with subtitles, we first conducted an online questionnaire with 102 participants. We used our findings to elicit requirements for a new approach called Adaptive Subtitles that allows the viewer to alter which speakers have subtitles displayed in real-time. We evaluated our approach with 19 participants to understand the interaction trade-offs and challenges within real-time adaptations of subtitled media. Our evaluation findings suggest that granular controls and structured onboarding allow viewers to make informed trade-offs when adapting media content, leading to improved viewing experiences.
Title: Gaze-Supported 3D Object Manipulation in Virtual Reality
Authors: family: Yu
given: Difeng; family: Lu
given: Xueshi; family: Shi
given: Rongkai; family: Liang
given: Hai-Ning; family: Dingler
given: Tilman; family: Velloso
given: Eduardo; family: Goncalves
given: Jorge
Venue: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
Keywords: gaze input, multimodal interface, 3D object manipulation

Abstract: This paper investigates integration, coordination, and transition strategies of gaze and hand input for 3D object manipulation in VR. Specifically, this work aims to understand whether incorporating gaze input can benefit VR object manipulation tasks, and how it should be combined with hand input for improved usability and efficiency. We designed four gaze-supported techniques that leverage different combination strategies for object manipulation and evaluated them in two user studies. Overall, we show that gaze did not offer significant performance benefits for transforming objects in the primary working space, where all objects were located in front of the user and within the arm-reach distance, but can be useful for a larger environment with distant targets. We further offer insights regarding combination strategies of gaze and hand input, and derive implications that can help guide the design of future VR systems that incorporate gaze input for 3D object manipulation.
Title: Facilitating Text Entry on Smartphones with QWERTY Keyboard for Users with Parkinson’s Disease
Authors: family: Wang
given: Yuntao; family: Yu
given: Ao; family: Yi
given: Xin; family: Zhang
given: Yuanwei; family: Chatterjee
given: Ishan; family: Patel
given: Shwetak; family: Shi
given: Yuanchun
Venue: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
Keywords: Parkinson’s disease, statistical decoding, QWERTY keyboard, touch model, text entry

Abstract: QWERTY is the primary smartphone text input keyboard configuration. However, insertion and substitution errors caused by hand tremors, often experienced by users with Parkinson’s disease, can severely affect typing efficiency and user experience. In this paper, we investigated Parkinson’s users’ typing behavior on smartphones. In particular, we identified and compared the typing characteristics generated by users with and without Parkinson’s symptoms. We then proposed an elastic probabilistic model for input prediction. By incorporating both spatial and temporal features, this model generalized the classical statistical decoding algorithm to correct insertion, substitution and omission errors, while maintaining direct physical interpretation. User study results confirmed that the proposed algorithm outperformed baseline techniques: users reached 22.8 WPM typing speed with a significantly lower error rate and higher user-perceived performance and preference. We concluded that our method could effectively improve the text entry experience on smartphones for users with Parkinson’s disease.
Title: Touch&Fold: A Foldable Haptic Actuator for Rendering Touch in Mixed Reality
Authors: family: Teng
given: Shan-Yuan; family: Li
given: Pengyu; family: Nith
given: Romain; family: Fonseca
given: Joshua; family: Lopes
given: Pedro
Venue: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
Keywords: Haptics, Mixed Reality, Wearable

Abstract: We propose a nail-mounted foldable haptic device that provides tactile feedback to mixed reality (MR) environments by pressing against the user's fingerpad when a user touches a virtual object. What is novel in our device is that it quickly tucks away when the user interacts with real-world objects. Its design allows it to fold back on top of the user's nail when not in use, keeping the user's fingerpad free to, for instance, manipulate handheld tools and other objects while in MR. To achieve this, we engineered a wireless and self-contained haptic device, which measures 24×24×41 mm and weighs 9.5 g. Furthermore, our foldable end-effector also features a linear resonant actuator, allowing it to render not only touch contacts (i.e., pressure) but also textures (i.e., vibrations). We demonstrate how our device renders contacts with MR surfaces, buttons, low- and high-frequency textures. In our first user study, we found that participants perceived our device to be more realistic than a previous haptic device that also leaves the fingerpad free (i.e., fingernail vibration). In our second user study, we investigated the participants’ experience while using our device in a real-world task that involved physical objects. We found that our device allowed participants to use the same finger to manipulate handheld tools, small objects, and even feel textures and liquids, without much hindrance to their dexterity, while feeling haptic feedback when touching MR interfaces.
Title: Elbow-Anchored Interaction: Designing Restful Mid-Air Input
Authors: family: Veras
given: Rafael; family: Singh
given: Gaganpreet; family: Farhadi-Niaki
given: Farzin; family: Udhani
given: Ritesh; family: Patekar
given: Parth Pradeep; family: Zhou
given: Wei; family: Irani
given: Pourang; family: Li
given: Wei
Venue: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
Keywords: Restful Input, Mid-air Gestures, Variable-posture Gestures, Comfort, Mid-air Gesture Fatigue, Elbow-anchored Input

Abstract: We designed a mid-air input space for restful interactions on the couch. We observed people gesturing in various postures on a couch and found that posture affects the choice of arm motions when no constraints are imposed by a system. Study participants that sat with the arm rested were more likely to use the forearm and wrist, as opposed to the whole arm. We investigate how a spherical input space, where forearm angles are mapped to screen coordinates, can facilitate restful mid-air input in multiple postures. We present two controlled studies. In the first, we examine how a spherical space compares with a planar space in an elbow-anchored setup, with a shoulder-level input space as baseline. In the second, we examine the performance of a spherical input space in four common couch postures that set unique constraints to the arm. We observe that a spherical model that captures forearm movement facilitates comfortable input across different seated postures.
Title: SonicHoop: Using Interactive Sonification to Support Aerial Hoop Practices
Authors: family: Liu
given: Wanyu; family: Dementyev
given: Artem; family: Schwarz
given: Diemo; family: Flety
given: Emmanuel; family: Mackay
given: Wendy E.; family: Beaudouin-Lafon
given: Michel; family: Bevilacqua
given: Frederic
Venue: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
Keywords: sound, Interactive sonification, capacitive sensing, auditory feedback, aerial hoop

Abstract: Aerial hoops are circular, hanging devices for both acrobatic exercise and artistic performance that let us explore the role of interactive sonification in physical activity. We present SonicHoop, an augmented aerial hoop that generates auditory feedback via capacitive touch sensing, thus becoming a digital musical instrument that performers can play with their bodies. We compare three sonification strategies through a structured observation study with two professional aerial hoop performers. Results show that SonicHoop fundamentally changes their perception and choreographic processes: instead of translating music into movement, they search for bodily expressions that compose music. Different sound designs affect their movement differently, and auditory feedback, regardless of type of sound, improves movement quality. We discuss opportunities for using SonicHoop as an aerial hoop training tool, as a digital musical instrument, and as a creative object; as well as using interactive sonification in other acrobatic practices to explore full-body vertical interaction.
Title: StickyPie: A Gaze-Based, Scale-Invariant Marking Menu Optimized for AR/VR
Authors: family: Ahn
given: Sunggeun; family: Santosa
given: Stephanie; family: Parent
given: Mark; family: Wigdor
given: Daniel; family: Grossman
given: Tovi; family: Giordano
given: Marcello
Venue: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
Keywords: head-worn display, eye gaze input, AR/VR, marking menu

Abstract: This work explores the design of marking menus for gaze-based AR/VR menu selection by expert and novice users. It first identifies and explains the challenges inherent in ocular motor control and current eye tracking hardware, including overshooting, incorrect selections, and false activations. Through three empirical studies, we optimized and validated design parameters to mitigate these errors while reducing completion time, task load, and eye fatigue. Based on the findings from these studies, we derived a set of design guidelines to support gaze-based marking menus in AR/VR. To overcome the overshoot errors found with eye-based expert marking menu behaviour, we developed StickyPie, a marking menu technique that enables scale-independent marking input by estimating saccade landing positions. An evaluation of StickyPie revealed that StickyPie was easier to learn than the traditional technique (i.e., RegularPie) and was 10% more efficient after 3 sessions.
Title: Radi-Eye: Hands-Free Radial Interfaces for 3D Interaction using Gaze-Activated Head-Crossing
Authors: family: Sidenmark
given: Ludwig; family: Potts
given: Dominic; family: Bapisch
given: Bill; family: Gellersen
given: Hans
Venue: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
Keywords: Gaze interaction, Augmented Reality, Eye tracking, Eye-Head Coordination, Virtual Reality, Radial Interface

Abstract: Eye gaze and head movement are attractive for hands-free 3D interaction in head-mounted displays, but existing interfaces afford only limited control. Radi-Eye is a novel pop-up radial interface designed to maximise expressiveness with input from only the eyes and head. Radi-Eye provides widgets for discrete and continuous input and scales to support larger feature sets. Widgets can be selected with Look & Cross, using gaze for pre-selection followed by head-crossing as trigger and for manipulation. The technique leverages natural eye-head coordination where eye and head move at an offset unless explicitly brought into alignment, enabling interaction without risk of unintended input. We explore Radi-Eye in three augmented and virtual reality applications, and evaluate the effect of radial interface scale and orientation on performance with Look & Cross. The results show that Radi-Eye provides users with fast and accurate input while opening up a new design space for hands-free fluid interaction.
Title: Hummer: Text Entry by Gaze and Hum
Authors: family: Hedeshy
given: Ramin; family: Kumar
given: Chandan; family: Menges
given: Raphael; family: Staab
given: Steffen
Venue: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
Keywords: hands-free interaction, eye typing, humming, swipe, eye tracking

Abstract: Text entry by gaze is a useful means of hands-free interaction that is applicable in settings where dictation suffers from poor voice recognition or where spoken words and sentences jeopardize privacy or confidentiality. However, text entry by gaze still shows inferior performance and it quickly exhausts its users. We introduce text entry by gaze and hum as a novel hands-free text entry. We review related literature to converge to word-level text entry by analysis of gaze paths that are temporally constrained by humming. We develop and evaluate two design choices: “HumHum” and “Hummer.” The first method requires short hums to indicate the start and end of a word. The second method interprets one continuous humming as an indication of the start and end of a word. In an experiment with 12 participants, Hummer achieved a commendable text entry rate of 20.45 words per minute, and outperformed HumHum and the gaze-only method EyeSwipe in both quantitative and qualitative measures.
Title: Communication Skills Training Intervention Based on Automated Recognition of Nonverbal Signals
Authors: family: Pereira
given: Monica; family: Hone
given: Kate
Venue: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
Keywords: Off-the-shelf emotion recognition technology, Media interviews, Social Signals, Communication skills training

Abstract: There have been promising studies that show a potential of providing social signal feedback to improve communication skills. However, these studies have primarily focused on unimodal methods of feedback. In addition to this, studies do not assess whether skills are maintained after a given time. With a sample size of 22 this paper investigates whether multimodal social signal feedback is an effective method of improving communication in the context of media interviews. A pre-post experimental evaluation of media skills training intervention is presented which compares standard feedback with augmented feedback based on automated recognition of multimodal social signals. Results revealed significantly different training effects between the two conditions. However, the initial experiment study failed to show significant differences in human judgement of performance. A 6-month follow-up study revealed human judgement ratings were higher for the experiment group. This study suggests that augmented selective multimodal social signal feedback is an effective method for communication skills training.
Title: EarRumble: Discreet Hands- and Eyes-Free Input by Voluntary Tensor Tympani Muscle Contraction
Authors: family: Röddiger
given: Tobias; family: Clarke
given: Christopher; family: Wolffram
given: Daniel; family: Budde
given: Matthias; family: Beigl
given: Michael
Venue: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
Keywords: tensor tympani muscle, hearables, subtle gestures, earables, in-ear barometry, discreet interaction

Abstract: We explore how discreet input can be provided using the tensor tympani - a small muscle in the middle ear that some people can voluntarily contract to induce a dull rumbling sound. We investigate the prevalence and ability to control the muscle through an online questionnaire (N=192) in which 43.2% of respondents reported the ability to “ear rumble”. Data collected from participants (N=16) shows how in-ear barometry can be used to detect voluntary tensor tympani contraction in the sealed ear canal. This data was used to train a classifier based on three simple ear rumble “gestures” which achieved 95% accuracy. Finally, we evaluate the use of ear rumbling for interaction, grounded in three manual, dual-task application scenarios (N=8). This highlights the applicability of EarRumble as a low-effort and discreet eyes- and hands-free interaction technique that users found “magical” and “almost telepathic”.
Title: SoloFinger: Robust Microgestures while Grasping Everyday Objects
Authors: family: Sharma
given: Adwait; family: Hedderich
given: Michael A.; family: Bhardwaj
given: Divyanshu; family: Fruchard
given: Bruno; family: McIntosh
given: Jess; family: Nittala
given: Aditya Shekhar; family: Klakow
given: Dietrich; family: Ashbrook
given: Daniel; family: Steimle
given: Jürgen
Venue: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
Keywords: microgesture, everyday objects, grasping, false activation

Abstract: Using microgestures, prior work has successfully enabled gestural interactions while holding objects. Yet, these existing methods are prone to false activations caused by natural finger movements while holding or manipulating the object. We address this issue with SoloFinger, a novel concept that allows design of microgestures that are robust against movements that naturally occur during primary activities. Using a data-driven approach, we establish that single-finger movements are rare in everyday hand-object actions and infer a single-finger input technique resilient to false activation. We demonstrate this concept’s robustness using a white-box classifier on a pre-existing dataset comprising 36 everyday hand-object actions. Our findings validate that simple SoloFinger gestures can relieve the need for complex finger configurations or delimiting gestures and that SoloFinger is applicable to diverse hand-object actions. Finally, we demonstrate SoloFinger’s high performance on commodity hardware using random forest classifiers.