huashen218/convxai-cia-dataset huggingface dataset:
Title: SonarID: Using Sonar to Identify Fingers on a Smartwatch
Authors: family: Kim
given: Jiwan; family: Oakley
given: Ian
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: Finger identification, smartwatch, sonar

Abstract: The diminutive size of wrist wearables has prompted the design of many novel input techniques to increase expressivity. Finger identification, or assigning different functionality to different fingers, has been frequently proposed. However, while the value of the technique seems clear, its implementation remains challenging, often relying on external devices (e.g., worn magnets) or explicit instructions. Addressing these limitations, this paper explores a novel approach to natural and unencumbered finger identification on an unmodified smartwatch: sonar. To do this, we adapt an existing finger tracking smartphone sonar implementation—rather than extract finger motion, we process raw sonar fingerprints representing the complete sonar scene recorded during a touch. We capture data from 16 participants operating a smartwatch and use their sonar fingerprints to train a deep learning recognizer that identifies taps by the thumb, index, and middle fingers with an accuracy of up to 93.7%, sufficient to support meaningful application development.
Title: SilentSpeller: Towards mobile, hands-free, silent speech text entry using electropalatography
Authors: family: Kimura
given: Naoki; family: Gemicioglu
given: Tan; family: Womack
given: Jonathan; family: Li
given: Richard; family: Zhao
given: Yuhui; family: Bedri
given: Abdelkareem; family: Su
given: Zixiong; family: Olwal
given: Alex; family: Rekimoto
given: Jun; family: Starner
given: Thad
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: wearable computing, text entry, silent speech interface

Abstract: Speech is inappropriate in many situations, limiting when voice control can be used. Most unvoiced speech text entry systems can not be used while on-the-go due to movement artifacts. Using a dental retainer with capacitive touch sensors, SilentSpeller tracks tongue movement, enabling users to type by spelling words without voicing. SilentSpeller achieves an average 97% character accuracy in offline isolated word testing on a 1164-word dictionary. Walking has little effect on accuracy; average offline character accuracy was roughly equivalent on 107 phrases entered while walking (97.5%) or seated (96.5%). To demonstrate extensibility, the system was tested on 100 unseen words, leading to an average 94% accuracy. Live text entry speeds for seven participants averaged 37 words per minute at 87% accuracy. Comparing silent spelling to current practice suggests that SilentSpeller may be a viable alternative for silent mobile text entry.
Title: ReflecTouch: Detecting Grasp Posture of Smartphone Using Corneal Reflection Images
Authors: family: Zhang
given: Xiang; family: Ikematsu
given: Kaori; family: Kato
given: Kunihiro; family: Sugiura
given: Yuta
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: Corneal reflection images., Hand grip detection

Abstract: By sensing how a user is holding a smartphone, adaptive user interfaces are possible such as those that automatically switch the displayed content and position of graphical user interface (GUI) components following how the phone is being held. We propose ReflecTouch, a novel method for detecting how a smartphone is being held by capturing images of the smartphone screen reflected on the cornea with a built-in front camera. In these images, the areas where the user places their fingers on the screen appear as shadows, which makes it possible to estimate the grasp posture. Since most smartphones have a front camera, this method can be used regardless of the device model; in addition, no additional sensor or hardware is required. We conducted data collection experiments to verify the classification accuracy of the proposed method for six different grasp postures, and the accuracy was 85%.
Title: FaceOri: Tracking Head Position and Orientation Using Ultrasonic Ranging on Earphones
Authors: family: Wang
given: Yuntao; family: Ding
given: Jiexin; family: Chatterjee
given: Ishan; family: Salemi Parizi
given: Farshid; family: Zhuang
given: Yuzhou; family: Yan
given: Yukang; family: Patel
given: Shwetak; family: Shi
given: Yuanchun
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: head orientation, earphone, head pose estimation., Acoustic ranging

Abstract: Face orientation can often indicate users’ intended interaction target. In this paper, we propose FaceOri, a novel face tracking technique based on acoustic ranging using earphones. FaceOri can leverage the speaker on a commodity device to emit an ultrasonic chirp, which is picked up by the set of microphones on the user’s earphone, and then processed to calculate the distance from each microphone to the device. These measurements are used to derive the user’s face orientation and distance with respect to the device. We conduct a ground truth comparison and user study to evaluate FaceOri’s performance. The results show that the system can determine whether the user orients to the device at a 93.5% accuracy within a 1.5 meters range. Furthermore, FaceOri can continuously track user’s head orientation with a median absolute error of 10.9 mm in the distance, 3.7° in yaw, and 5.8° in pitch. FaceOri can allow for convenient hands-free control of devices and produce more intelligent context-aware interactions.
Title: More Errors vs. Longer Commands: The Effects of Repetition and Reduced Expressiveness on Input Interpretation Error, Learning, and Effort
Authors: family: Lam
given: Kevin C.; family: Gutwin
given: Carl; family: Klarkowski
given: Madison; family: Cockburn
given: Andy
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: input error, interpretation error, error correction, input expressiveness

Abstract: Many interactive systems are susceptible to misinterpreting the user’s input actions or gestures. Interpretation errors are common when systems gather a series of signals from the user and then attempt to interpret the user’s intention based on those signals – e.g., gesture identification from a touchscreen, camera, or body-worn electrodes – and previous work has shown that interpretation error can cause significant problems for learning new input commands. Error-reduction strategies from telecommunications, such as repeating a command or increasing the length of the input while reducing its expressiveness, could improve these input mechanisms – but little is known about whether longer command sequences will cause problems for users (e.g., increased effort or reduced learning). We tested performance, learning, and perceived effort in a crowd-sourced study where participants learned and used input mechanisms with different error-reduction techniques. We found that error reduction techniques are feasible, can outperform error-prone ordinary input, and do not negatively affect learning or perceived effort.
Title: ShapeFindAR: Exploring In-Situ Spatial Search for Physical Artifact Retrieval using Mixed Reality
Authors: family: Stemasov
given: Evgeny; family: Wagner
given: Tobias; family: Gugenheimer
given: Jan; family: Rukzio
given: Enrico
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: 3D-Printing, Personal Fabrication, Spatial Search, In-Situ Search, Mixed Reality, Model Repositories, Physical Artifact Retrieval

Abstract: Personal fabrication is made more accessible through repositories like Thingiverse, as they replace modeling with retrieval. However, they require users to translate spatial requirements to keywords, which paints an incomplete picture of physical artifacts: proportions or morphology are non-trivially encoded through text only. We explore a vision of in-situ spatial search for (future) physical artifacts, and present ShapeFindAR, a mixed-reality tool to search for 3D models using in-situ sketches blended with textual queries. With ShapeFindAR, users search for geometry, and not necessarily precise labels, while coupling the search process to the physical environment (e.g., by sketching in-situ, extracting search terms from objects present, or tracing them). We developed ShapeFindAR for HoloLens 2, connected to a database of 3D-printable artifacts. We specify in-situ spatial search, describe its advantages, and present walkthroughs using ShapeFindAR, which highlight novel ways for users to articulate their wishes, without requiring complex modeling tools or profound domain knowledge.
Title: Investigating Potentials of Shape-Changing Displays for Sound Zones
Authors: family: Johansen
given: Stine S; family: Merritt
given: Timothy; family: Jacobsen
given: Rune Møberg; family: Nielsen
given: Peter Axel; family: Kjeldskov
given: Jesper
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: shape-changing interfaces, soundscape, Sound zone

Abstract: In this paper, we investigate the use of shape-change for interaction with sound zones. A core challenge to designing interaction with sound zone systems is to support users’ understanding of the unique spatial properties of sound zones. Shape-changing interfaces present new opportunities for addressing this. We present a structured investigation into this. We leveraged the knowledge of 12 sound experts to define a set of basic shapes and movements. Then, we constructed a prototype and conducted an elicitation study with 17 novice users, investigating the experience of these shapes and movements. Our findings show that physical visualizations of sound zones can be useful in supporting users’ experience of sound zones. We present a framework of 4 basic pattern categories that prompt different sound zone experiences and outline further research directions for shape-change in supporting sound zone interaction.
Title: Do You See What I Hear? — Peripheral Absolute and Relational Visualisation Techniques for Sound Zones
Authors: family: Jacobsen
given: Rune Møberg; family: van Berkel
given: Niels; family: Skov
given: Mikael B.; family: Johansen
given: Stine S; family: Kjeldskov
given: Jesper
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: visualisation, ubiquitous computing, sound visualisation, sound interaction, Sound zones

Abstract: Sound zone technology allows multiple simultaneous sound experiences for multiple people in the same room without interference. However, given the inherent invisible and intangible nature of sound zones, it is unclear how to communicate the position and size of sound zones to users. This paper compares two visualisation techniques; absolute visualisation, relational visualisation, as well as a baseline condition without visualisations. In a within-subject experiment (N = 33), we evaluated these techniques for effectiveness and efficiency across four representative tasks. Our findings show that the absolute and relational visualisation techniques increase effectiveness in multi-user tasks but not in single-user tasks. The efficiency for all tasks was improved using visualisations. We discuss the potential of visualisations for sound zones and highlight future research opportunities for sound zone interaction.
Title: Consent in the Age of AR: Investigating The Comfort With Displaying Personal Information in Augmented Reality
Authors: family: Rixen
given: Jan Ole; family: Colley
given: Mark; family: Askari
given: Ali; family: Gugenheimer
given: Jan; family: Rukzio
given: Enrico
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: Mixed Reality, Consent, Data Glasses, Personal Information, Augmented Reality, Public Experiences, Comfort, Social Acceptability, User Acceptance, Disclosure

Abstract: Social Media (SM) has shown that we adapt our communication and disclosure behaviors to available technological opportunities. Head-mounted Augmented Reality (AR) will soon allow to effortlessly display the information we disclosed not isolated from our physical presence (e.g., on a smartphone) but visually attached to the human body. In this work, we explore how the medium (AR vs. Smartphone), our role (being augmented vs. augmenting), and characteristics of information types (e.g., level of intimacy, self-disclosed vs. non-self-disclosed) impact the users’ comfort when displaying personal information. Conducting an online survey (N=148), we found that AR technology and being augmented negatively impacted this comfort. Additionally, we report that AR mitigated the effects of information characteristics compared to those they had on smartphones. In light of our results, we discuss that information augmentation should be built on consent and openness, focusing more on the comfort of the augmented rather than the technological possibilities.
Title: “Should I visit the clinic”: Analyzing WhatsApp-mediated Online Health Support for Expectant and New Mothers in Rural India
Authors: family: Yadav
given: Deepika; family: Dabas
given: Kirti; family: Malik
given: Prerna; family: Bhandari
given: Anushka; family: Singh
given: Pushpendra
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: Social support, Maternal health, WhatsApp, Digital support group

Abstract: Limited interaction with professionals, infrastructural, and social constraints put barriers in providing holistic support to expectant and new mothers in low-resource settings. We examine the use of digital support groups facilitated through WhatsApp by a non-government organization in India. Complementing prior research, these digital peer support groups inform about an open public space created over a chat platform where rural communities and health professionals can engage. By qualitatively analyzing six months of interaction among 588 group members and collecting the experiences of the group moderators, we inform about how the support groups acted as an important source for compensating the gaps in the existing healthcare, providing reassurance support on routine health, explanation on test reports, validation and counseling support in ongoing treatments. We also derive implications for the future of digital support groups and the need for further research on the use of unplatformed design models in resource-constrained settings.
Title: Dare to Dream, Dare to Livestream: How E-Commerce Livestreaming Empowers Chinese Rural Women
Authors: family: Tang
given: Ningjing; family: Tao
given: Lei; family: Wen
given: Bo; family: Lu
given: Zhicong
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: empowerment, livestreaming, rural computing, feminism

Abstract: China has witnessed rapid growth in its e-commerce markets and livestreaming communities in recent years. The commercialization of livestreaming has led to the rise of e-commerce livestreamers, among which rural women constitute a substantial portion. To understand the motivations underlying these women's choices to engage in livestreaming activities and probe the extent to which they are empowered by this new form of entrepreneurship, we conducted an interview-based study with rural female livestreamers. We found that these women chose to be livestreamers for practical and self-presentation purposes and they gained a sense of self-empowerment through economic, social, intellectual, psychological, and spiritual dimensions. At the same time, however, they experienced and confronted social stigmas rooted in rural societies and the strategies they used to deal with these biases were vastly different. Our work contributes to the HCI community by providing a nuanced understanding of the motives and lived experiences of rural female livestreamers and offers design implications that could improve the everyday experiences of these livestreamers.
Title: Feeling Proud, Feeling Embarrassed: Experiences of Low-income Women with Crowd Work
Authors: family: Varanasi
given: Rama Adithya; family: Siddarth
given: Divya; family: Seshadri
given: Vivek; family: Bali
given: Kalika; family: Vashistha
given: Aditya
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: HCI4D, Women, crowdsourcing work, mobile crowdsourcing, crowd work, crowdsourcing app

Abstract: Women’s economic empowerment is central to gender equality. However, work opportunities available to low-income women in patriarchal societies are infrequent. While crowd work has the potential to increase labor participation of such women, much remains unknown about their engagement with crowd work and the resultant opportunities and tensions. To fill this gap, we critically examined the adoption and use of a crowd work platform by low-income women in India. Through a qualitative study, we found that women faced tremendous challenges, for example, in seeking permission from family members to do crowd work, lack of family support and encouragement, and often working in unfavorable environments where they had to hide their work lives. While crowd work took a toll on their physical and emotional wellbeing, it also led to increased confidence, agency, and autonomy. We discuss ways to reduce frictions and tensions in participation of low-income women on crowd work platforms.
Title: Coordination and Collaboration: How do Volunteer Moderators Work as a Team in Live Streaming Communities?
Authors: family: Cai
given: Jie; family: Wohn
given: Donghee Yvette
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: Teamwork, live streaming, online community, collaboration, rules and norms, content moderation, volunteer mods, coordination

Abstract: Volunteer moderators (mods) play significant roles in developing moderation standards and dealing with harmful content in their micro-communities. However, little work explores how volunteer mods work as a team. In line with prior work about understanding volunteer moderation, we interview 40 volunteer mods on Twitch — a leading live streaming platform. We identify how mods collaborate on tasks (off-streaming coordination and preparation, in-stream real-time collaboration, and relationship building both off-stream and in-stream to reinforce collaboration) and how mods contribute to moderation standards (collaboratively working on the community rulebook and individually shaping community norms). We uncover how volunteer mods work as an effective team. We also discuss how the affordances of multi-modal communication and informality of volunteer moderation contribute to task collaboration, standards development, and mod’s roles and responsibilities.
Title: Shared User Interfaces of Physiological Data: Systematic Review of Social Biofeedback Systems and Contexts in HCI
Authors: family: Moge
given: Clara; family: Wang
given: Katherine; family: Cho
given: Youngjun
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: physiological data sharing, Physiological computing, systematic review, computer-mediated communication, emotion communication, social biofeedback

Abstract: As an emerging interaction paradigm, physiological computing is increasingly being used to both measure and feed back information about our internal psychophysiological states. While most applications of physiological computing are designed for individual use, recent research has explored how biofeedback can be socially shared between multiple users to augment human-human communication. Reflecting on the empirical progress in this area of study, this paper presents a systematic review of 64 studies to characterize the interaction contexts and effects of social biofeedback systems. Our findings highlight the importance of physio-temporal and social contextual factors surrounding physiological data sharing as well as how it can promote social-emotional competences on three different levels: intrapersonal, interpersonal, and task-focused. We also present the Social Biofeedback Interactions framework to articulate the current physiological-social interaction space. We use this to frame our discussion of the implications and ethical considerations for future research and design of social biofeedback interfaces.
Title: From Who You Know to What You Read: Augmenting Scientific Recommendations with Implicit Social Networks
Authors: family: Kang
given: Hyeonsu B; family: Kocielnik
given: Rafal; family: Head
given: Andrew; family: Yang
given: Jiangjiang; family: Latzke
given: Matt; family: Kittur
given: Aniket; family: Weld
given: Daniel S; family: Downey
given: Doug; family: Bragg
given: Jonathan
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems

Abstract: The ever-increasing pace of scientific publication necessitates methods for quickly identifying relevant papers. While neural recommenders trained on user interests can help, they still result in long, monotonous lists of suggested papers. To improve the discovery experience we introduce multiple new methods for augmenting recommendations with textual relevance messages that highlight knowledge-graph connections between recommended papers and a user’s publication and interaction history. We explore associations mediated by author entities and those using citations alone. In a large-scale, real-world study, we show how our approach significantly increases engagement—and future engagement when mediated by authors—without introducing bias towards highly-cited authors. To expand message coverage for users with less publication or interaction history, we develop a novel method that highlights connections with proxy authors of interest to users and evaluate it in a controlled lab study. Finally, we synthesize design implications for future graph-based messages.
Title: Follow the Leader: Technical and Inspirational Leadership in Open Source Software
Authors: family: Hergueux
given: Jérôme; family: Kessler
given: Samuel
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: Communication, Leadership, Open Source Software, Virtual Teams

Abstract: We conduct the first comprehensive study of the behavioral factors which predict leader emergence within open source software (OSS) virtual teams. We leverage the full history of developers’ interactions with their teammates and projects at github.com between January 2010 and April 2017 (representing about 133 million interactions) to establish that – contrary to a common narrative describing open source as a pure “technical meritocracy” – developers’ communication abilities and community building skills are significant predictors of whether they emerge as team leaders. Inspirational communication therefore appears as central to the process of leader emergence in virtual teams, even in a setting like OSS, where technical contributions have often been conceptualized as the sole pathway to gaining community recognition. Those results should be of interest to researchers and practitioners theorizing about OSS in particular and, more generally, leadership in geographically dispersed virtual teams, as well as to online community managers.