Miracle-dz/UniFAR-FTUs huggingface dataset:
Neural representations of non-native speech reflect proficiency and interference from native language knowledge

Learning to process speech in a foreign language involves learning new representations for mapping the auditory signal to linguistic structure. Behavioral experiments suggest that even listeners that are highly proficient in a non-native language experience interference from representations of their native language. However, much of the evidence for such interference comes from tasks that may inadvertently increase the salience of native language competitors. Here we tested for neural evidence of proficiency and native language interference in a naturalistic story listening task. We studied electroencephalography responses of native Dutch listeners to an English short story, spoken by a native speaker of either American English or Dutch. We modeled brain responses with multivariate temporal response functions, using acoustic and language models. We found evidence for activation of Dutch language statistics when listening to English, but only when it was spoken with a Dutch accent. This suggests that a naturalistic, monolingual setting decreases the interference from native language representations, whereas an accent in the listeners’ own native language may increase native language interference, by increasing the salience of the native language and activating native language phonetic and lexical representations. Brain responses suggest that words from the native language compete with the foreign language in a single word recognition system, rather than being activated in a parallel lexicon. We further found that secondary acoustic representations of speech (after 200 ms latency) decreased with increasing proficiency. This may reflect improved acoustic-phonetic models in more proficient listeners.
GAMM: Graph-Based Agile Multidimensional Model

The advent of big data has continuously offered new opportunities for analysis due to the growth and diversification of data sources. However, traditional data warehouses based on multidimensional models have limitations when it comes to changing and evolving. In recent years, innovative work in the field of data warehouse evolution has been performed; it has mainly focused on the management of big data and the chronological evolution of models in terms of their structures and data. However, an agile decision model is still required. We propose in this paper an agile approach for schema evolution in data warehouses that allows designers to integrate new data sources and take into account new user needs in order to enrich the analysis possibilities of data warehouses in a flexible way. Our approach is based on a multi-version evolutionary schema model. The data instances corresponding to the different versions of the schema are stored in a graph data warehouse. A meta-model will allow the management of the warehouse schema versions. We also propose evolution functions on the schema level. We validate our approach with a software prototype and a case study that illustrates queries on schema versions, cross-queries and the runtime of our approach.
Distributed System for Predicting Malicious Activity in Computer Networks

This article introduce a self-organized that based on deep learning (DL) algorithms. A new self-organized incremental neural network FG-SOINN presented in the Python programming language. This self-organized neural network (SOINN) algorithm generates packets of nodes and edges that are cleaned through fixed, user-defined time intervals. This leads to sudden changes in the network structure. This is due to the fact that large regions of the network are removed with a fixed period before the resumption of the training. Such "oblivion" conflicts with a more gradual oblivion on a large period of time, which is usually observed in natural cognitive systems. In a self-organized incremental algorithm, the removal of nodes and edges is determined by two parameters. These settings should be improved for each existing program through cross-checking. This article proves that FG-SOINN significantly eliminates this shortcoming, considering removal of nodes and edges as a necessary part of the process of study. Three concepts have been developed and implemented to form FG: Time of idle nodes and edges, reliability and utility of a particular node or edges. It is using these concepts that this algorithm and system will remove nodes and fins. The FG technique or node wear technique determines when and after which node of the period it will be removed. But if they are not updated in the specified time, they are simply deleted. These characteristics make it attractive for the dynamics of the environment, which requires long-term training. To ensure system scalability, the network will be guided by the n parameter. The algorithm starts its work and initiates the network with empty sets of nodes.Next, the nodes are added to the weight vectors. After that, the winner vector (nearest node) and the second winner vector will be searched. Distance measurement formulas will be used to determine the distance. The structure and results of the system demonstrate that this proposition can be adapted to the dynamic profile of network data for both normal and attack classes. The algorithm uses less resources, is faster, and has a higher detection rate than the teaching-teacher method than the traditional SOINN.
Establishing Awareness through Pointing Gestures during Collaborative Decision-Making in a Wall-Display Environment

Sharing a physical environment, such as that of a wall-display, facilitates gaining awareness of others’ actions and intentions, thereby bringing benefits for collaboration. Previous studies have provided first insights on awareness in the context of tabletops or smaller vertical displays. This paper seeks to advance the current understanding on how users share awareness information in wall-display environments and focusses on mid-air pointing gestures as a foundational part of communication. We present a scenario dealing with the organization of medical supply chains in crisis situations, and report on the results of a user study with 24 users, split into 6 groups of 4, performing several tasks. We investigate pointing gestures and identify three subtypes used as awareness cues during face-to-face collaboration: narrative pointing, loose pointing, and sharp pointing. Our observations show that reliance on gesture subtypes varies across participants and groups, and that sometimes vague pointing is sufficient to support verbal negotiations.
“This Could Be The Day I Die”: Unpacking Interpersonal and Systems Trust in a Local Sharing Economy Community

The rapid development of the “sharing economy” enables the effective and efficient coordination, acquisition, distribution, and sharing of many kinds of different resources. Beyond the well-known sharing economy services such as Airbnb and Uber, an increasing number of local sharing initiatives have established online platforms and services to facilitate access to the shared resources within their local communities. With the automation and complexity of digital tools and platforms, and the specific challenges of online sharing communities, users’ trust and reliance become increasingly critical for successful use and adoption. In our qualitative study in collaboration with two industry partners (a local sharing community and a large infrastructure provider in Switzerland), we unpack various perspectives of interpersonal trust in the community and the systems trust of the supporting technologies. On this basis, we elicited a set of design opportunities for future platforms in the context of sharing economy.
Textile Game Controller: Smart knee pads for Therapeutic Exercising 

In the field of physiotherapy and rehabilitation, location-independent training has gained importance. We present the further development of a wearable for this purpose including gamification to improve successful training. A wearable was developed to increase the motivation of patients to perform their prescribed physical therapy exercises at home. Extending a pair of smart trousers [12], smart knee pads connected to a gaming app were developed. A comparative qualitative study was conducted in order to explore how users react to playing a game as an extension of their physiotherapy session. The results of the user test show that the majority of respondents consider technology-enabled training to be helpful for their therapy success. Aspects of a "playful approach" and "competition" were named as the main motivating factors for the use of wearables in a therapy context. However, "competition" was only rated positively by male participants.
Dis/Immersion in Mindfulness Meditation with a Wandering Voice Assistant

Mindfulness meditation is a validated means of helping people manage stress. Voice-based virtual assistants (VAs) in smart speakers, smartphones, and smart environments can assist people in carrying out mindfulness meditation through guided experiences. However, the common fixed location embodiment of VAs makes it difficult to provide intuitive support. In this work, we explored the novel embodiment of a "wandering voice" that is co-located with the user and “moves” with the task. We developed a multi-speaker VA embedded in a yoga mat that changes location along the body according to the meditation experience. We conducted a qualitative user study in two sessions, comparing a typical fixed smart speaker to the wandering VA embodiment. Thick descriptions from interviews with twelve people revealed sometimes simultaneous experiences of immersion and dis-immersion. We offer design implications for "wandering voices" and a new paradigm for VA embodiment that may extend to guidance tasks in other contexts.
ThermalPen: Adding Thermal Haptic Feedback to 3D Sketching

Sketching in virtual 3D environments has enabled new forms of artistic expression and a variety of novel design use-cases. However, the lack of haptic feedback proves to be one of the main challenges in this field. While prior work has investigated vibrotactile and force-feedback devices, this paper proposes the addition of thermal feedback. We present ThermalPen, a novel pen for 3D sketching that associates the texture and colour of strokes with different thermal properties. For example, a fire texture elicits an increase in temperature, while an ice texture causes a temperature drop in the pen. Our goal with ThermalPen is to enhance the 3D sketching experience and allow users to use this tool to increase their creativity while sketching. We plan on evaluating the influence of thermal feedback on the 3D sketching experience, with a focus on user creativity in the future.
The “Three-Legged Stool": Designing for Equitable City, Community, and Research Partnerships in Urban Environmental Sensing

Urban environmental monitoring campaigns depend on expertise from city agencies, residents, and researchers. Deployment efforts rarely include all three stakeholders, typically leading to initiatives that struggle to produce credible, actionable data. We describe the implementation of a large-scale, long-term air quality sensing network in Chicago Illinois; detail stakeholder interviews and meetings; and present three interfaces—–a website accessible via in-situ QR codes, APIs, and a mobile, mixed-media experience. We show how a collaborative approach created a more equitable sensor distribution compared to crowdsourced or regulatory designs. We highlight shared goals of education, engagement, and empowerment despite the diversity of tool and analytics needs across stakeholder groups. Reflecting on our work, we develop a “three-legged stool” framework representing the criticality of balanced participation from three key stakeholder groups—city, community, and research—in deploying novel urban technologies. This approach can help HCI researchers facilitate more democratic technology deployments in urban spaces.
Safety intelligent relay node selection algorithm based on EH-WSN

The open, distributed, and dynamic nature of wireless sensor networks makes them vulnerable to network attacks. Meanwhile, the limited energy of nodes and the existence of selfish nodes will lead to a low packet delivery rate and high energy consumption. In order to solve these problems, a safety intelligent relay node selection algorithm based on EH-WSN is proposed. First, we implemented a solar replenishment model to predict the node's replenishment energy. Then, by establishing a relay node evaluation model, the node on the routing path is evaluated, and the node evaluation value is updated dynamically in route training based on an enhanced Q-Learning algorithm. The simulation results show that the proposed algorithm has good performance in terms of improving packet delivery rates and reducing the energy consumption of nodes.
“Easier or Harder, Depending on Who the Hearing Person Is”: Codesigning Videoconferencing Tools for Small Groups with Mixed Hearing Status

With improvements in automated speech recognition and increased use of videoconferencing, real-time captioning has changed significantly. This shift toward broadly available but less accurate captioning invites exploration of the role hearing conversation partners play in shaping the accessibility of a conversation to d/Deaf and hard of hearing (DHH) captioning users. While recent work has explored DHH individuals’ videoconferencing experiences with captioning, we focus on established groups’ current practices and priorities for future tools to support more accessible online conversations. Our study consists of three codesign sessions, conducted with four groups (17 participants total, 10 DHH, 7 hearing). We found that established groups crafted social accessibility norms that met their relational contexts. We also identify promising directions for future captioning design, including the need to standardize speaker identification and customization, opportunities to provide behavioral feedback during a conversation, and ways that videoconferencing platforms could enable groups to set and share norms.
Assessing Mapper Conflict in OpenStreetMap Using the Delphi Survey Method

Studies of mapper conflict in OpenStreetMap (OSM) have focused exclusively on cartographic vandalism and its effect on data quality. This paper takes a broader view on mapper conflict in OSM. Using a Delphi survey method, we collect qualitative data on perceived conflict from long-time OSM mappers. We ask mappers about four aspects of conflict in OSM: (1) topic of conflict, (2) factors leading to conflict, (3) effects of conflict, and (4) potential conflict management methods. Our results show that conflict in OSM can be explained by clashing values and opinions within and across different mapper subgroups and can be exacerbated by negative mapper behaviors. The boundaries of these subgroups, while implicit, are often defined by gender, mappers’ geographic location, level of expertise, and mappers’ professional affiliation. Based on these results, we discuss design options for OSM’s existing public communication channels that often become foci of mapper conflict management.
Lyric App Framework: A Web-based Framework for Developing Interactive Lyric-driven Musical Applications

Lyric videos have become a popular medium to convey lyrical content to listeners, but they present the same content whenever they are played and cannot adapt to listeners’ preferences. Lyric apps, as we name them, are a new form of lyric-driven visual art that can render different lyrical content depending on user interaction and address the limitations of static media. To open up this novel design space for programmers and musicians, we present Lyric App Framework, a web-based framework for building interactive graphical applications that play musical pieces and show lyrics synchronized with playback. We designed the framework to provide a streamlined development experience for building production-ready lyric apps with creative coding libraries of choice. We held programming contests twice and collected 52 examples of lyric apps, enabling us to reveal eight representative categories, confirm the framework’s effectiveness, and report lessons learned.
Examining Gender-oriented Design Features in Computational Toys and Kits for Young Children

Computational toys and apps, or coding kits, are the primary learning media for young children to engage in Computational Thinking concepts and skills. However, how coding kits are designed to welcome children of different genders remains unclear, a critical research gap given that computing is mostly a male-dominated field. Drawing on relevant literature, we develop a framework of gender-related design features in toys (i.e., boy-oriented, girl-oriented, or gender-neutral features) and employ it to examine gender-related design features in commercially available coding kits for young children aged seven and under (N=110). The findings reveal the lopsided gender representation in coding kits, e.g., their physical forms and supported coding activities are predominantly boy-oriented. We discuss design and research implications for coding kits to welcome participation from children of different genders, especially young girls whose preferred design features are underrepresented in current designs.
Enabling Haptic Experiences Anywhere, Anytime

While seminal screen-based computing technologies (e.g., desktop or VR/AR headsets) have evolved to respond to users’ needs for extreme freedom and mobility, the same cannot be said about rich haptic experiences (e.g., those that allow users to feel touch and forces). In my research I trace back the possible root causes to the way that haptic devices are engineered—to deliver realistic & immersive sensations, haptics devices use large actuators, which leads to two interface issues: (1) cumbersome form-factors that obstruct the user's body and prevent users from engaging in other dexterous tasks; and (2) extreme power consumption that causes these devices to have a short-lived life or even be tethered—all of which are incompatible with the users’ needs and desires for freedom and mobility. The consequence of these two issues is that, as of now, haptics is mostly a tool for VR, but is absent from other interactive contexts, especially those where users move freely and interact with everyday tools (e.g., AR). As such, in my research I posit we need to redesign haptic devices with users in mind rather than only guided by the metric of virtual haptic realism. As such, I propose that (1) haptic devices need to play well with everyday tasks (e.g., they cannot prevent users from interacting with their loved ones or with their everyday tools), and (2) haptic devices need to be always available (without the need for bulky batteries or cables). In the following, I demonstrate two examples of wearable haptic devices that I engineered to illustrate that these goals are not just possible but desirable.
Toucha11y: Making Inaccessible Public Touchscreens Accessible

Despite their growing popularity, many public kiosks with touchscreens are inaccessible to blind people. Toucha11y is a working prototype that allows blind users to use existing inaccessible touchscreen kiosks independently and with little effort. Toucha11y consists of a mechanical bot that can be instrumented to an arbitrary touchscreen kiosk by a blind user and a companion app on their smartphone. The bot, once attached to a touchscreen, will recognize its content, retrieve the corresponding information from a database, and render it on the user’s smartphone. As a result, a blind person can use the smartphone’s built-in accessibility features to access content and make selections. The mechanical bot will detect and activate the corresponding touchscreen interface. We present the system design of Toucha11y along with a series of technical evaluations. Through a user study, we found out that Toucha11y could help blind users operate inaccessible touchscreen devices.
Modeling and Improving Text Stability in Live Captions

In recent years, live captions have gained significant popularity through its availability in remote video conferences, mobile applications, and the web. Unlike preprocessed subtitles, live captions require real-time responsiveness by showing interim speech-to-text results. As the prediction confidence changes, the captions may update, leading to visual instability that interferes with the user’s viewing experience. In this paper, we characterize the stability of live captions by proposing a vision-based flickering metric using luminance contrast and Discrete Fourier Transform. Additionally, we assess the effect of unstable captions on the viewer through task load index surveys. Our analysis reveals significant correlations between the viewer’s experience and our proposed quantitative metric. To enhance the stability of live captions without compromising responsiveness, we propose the use of tokenized alignment, word updates with semantic similarity, and smooth animation. Results from a crowdsourced study (N=123), comparing four strategies, indicate that our stabilization algorithms lead to a significant reduction in viewer distraction and fatigue, while increasing viewers’ reading comfort.
Not Merely Deemed as Distraction: Investigating Smartphone Users’ Motivations for Notification-Interaction

Notifications are commonly considered a distraction when they arrive during a task, and consequently, prior research has consistently sought effective ways of deferring their arrival until task transitions. However, many smartphone users still interact with notifications during tasks. In our qualitative study combining diary study and semi-structured interviews, we examined 34 research participants’ motivations for interacting with smartphone notifications at different times, including during tasks. Our findings resulted in a human-notification interaction framework comprised of 12 unique motivations frequently associated with three activity timings for interacting with notifications, including before-task, during-task, and after-task. Notably, participants frequently perceived interaction with notifications as a tool for improving task performance, making the most of their time, and promoting personal well-being, rather than only as a distraction. The before-the-task timing, in particular, has received little attention in previous research and deserves more attention as it was related to specific user motivations for notification interaction.
Designing for Inclusivity and Accessibility of Mental Health Technologies

Mental health has been a serious concern among university students, and minority students are known to be particularly vulnerable due to underutilization of mental health services and unfamiliarity with Western health care approaches. My research explores the accessibility and inclusivity of mental health technologies, mainly focusing on how the perspectives and experiences of university students of diverse cultural backgrounds, visible minorities, and international students can inform more inclusive designs. In my first study, I uncovered cultural and communication barriers that suggest that more scaffolding is needed for these students to engage with technologies for their mental health, including supporting storytelling and skill learning from peers as well as providing cultural support and representation. In my second study, I co-designed with campus mental health experts and international students to understand what features and support they desired in these technologies, discovering that stories once again featured heavily in their ideas. For the next two studies, I plan to build and evaluate prototypes that feature a novel storytelling peer support platform.