User interface personalization enhances digital efficiency, usability, and accessibility. However, in user-driven setups, limited support for identifying and evaluating worthwhile opportunities often leads to underuse. We explore a reflexive personalization approach where individuals engage with their digital interaction data to identify meaningful personalization opportunities and benefits. We interviewed 12 participants, using experimental vignettes as design probes to support reflection on different forms of using interaction data to empower decision-making in personalization and the preferred level of system support. We found that people can independently identify personalization opportunities but prefer system support through visual personalization suggestions. Interaction data can shape how users perceive and approach personalization by reinforcing the perceived value of change and data collection, helping them weigh benefits against effort, and increasing the transparency of system suggestions. We discuss opportunities for designing personalization software that raises end-users’ agency over interfaces through reflective engagement with their interaction data.

With the ubiquitous use of mobile applications, it is paramount that they are accessible, so they can empower all users, including those with different needs. Determining if an app is accessible implies conducting an accessibility evaluation. While accessibility evaluations have been thoroughly studied in the web domain, there are still many open questions when evaluating mobile applications. This paper investigates mobile accessibility evaluation methodologies. We conducted four studies, including an examination of accessibility reports from European Member-states, interviews with accessibility experts, manual evaluations, and usability tests involving users. Our investigations have uncovered significant limitations in current evaluation methods, suggesting that the absence of authoritative guidelines and standards, similar to what exists for the web, but tailored specifically to mobile devices, hampers the effectiveness of accessibility evaluation and monitoring activities. Based on our findings, we present a set of recommendations aimed at improving the evaluation methodologies for assessing mobile applications’ accessibility.

Many Virtual Reality (VR) locomotion techniques have been proposed, but those explored for and with blind people are often custom-made or require specialized equipment. Consequently, it is unclear how popular techniques can support blind people’s VR locomotion, blocking access to most VR experiences. We implemented three popular techniques — Arm Swinging, Linear Movement (joystick-based steering), and Point & Teleport — with minor adaptations for accessibility. We conducted a study with 14 blind participants consisting of navigation tasks with these techniques and a semi-structured interview. We found no differences in overall performance (e.g., completion time), but contrasting preferences. Findings highlight the challenges and advantages of each technique and participants’ strategies. We discuss, among others, how augmenting the techniques enabled blind people to navigate in VR, the greater control of movement of Arm Swinging, the simplicity and familiarity of Linear Movement, and the potential for efficiency and for scanning the environment of Point & Teleport.

Abstract Charts remain widely inaccessible on the web for users of assistive technologies like screen readers. This is, in part, due to data visualization experts still lacking the experience, knowledge, and time to consistently implement accessible charts. As a result, screen reader users are prevented from accessing information and are forced to resort to tabular alternatives (if available), limiting the insights that they can gather. We worked with both groups to develop AutoVizuA11y, a tool that automates the addition of accessible features to web‐based charts. It generates human‐like descriptions of the data using a large language model, calculates statistical insights from the data, and provides keyboard navigation between multiple charts and underlying elements. Fifteen screen reader users interacted with charts made accessible with AutoVizuA11y in a usability test, thirteen of which praised the tool for its intuitive design, short learning curve, and rich information. On average, they took 66 seconds to complete each of the eight analytical tasks presented and achieved a success rate of 89%. Through a SUS questionnaire, the participants gave AutoVizuA11y an “Excellent” score — 83.5/100 points. We also gathered feedback from two data visualization experts who used the tool. They praised the tool availability, ease of use and functionalities, and provided feedback to add AutoVizuA11y support for other technologies in the future.

User-generated content plays a key role in social networking, allowing a more active participation, socialisation, and collaboration among users. In particular, media content has been gaining a lot of ground, allowing users to express themselves through different types of formats such as images, GIFs and videos. The majority of this growing type of online visual content remains inaccessible to a part of the population, in particular for those who have a visual disability, despite available tools to mitigate this source of exclusion. We sought to understand how people are perceiving this type of online content in their networks and how support tools are being used. To do so, we conducted a user study, with 258 social network users through an online questionnaire, followed by interviews with 20 of them – 7 blind users and 13 sighted users. Results show how the different approaches being employed by major platforms may not be sufficient to address this issue properly. Our findings reveal that users are not always aware of the possibility and the benefits of adopting accessible practices. From the general perspectives of end-users experiencing accessible practices, concerning barriers encountered, and motivational factors, we also discuss further approaches to create more user engagement and awareness.

This special issue highlights 11 papers from the ACM Intelligent User Interface (IUI) 2017 international conference, which received 272 submissions and of which 63 of them were accepted by the program committee (acceptance rate: 23%).The 11 articles in this special issue of TiiS were selected by the program committee to be among the best papers accepted into the program of ACM IUI 2017.Each of these selected conference papers was extended, with at least 30% new materials in the new version, which allowed authors to elaborate on their excellent lines of research relevant to the ACM IUI community.The extended versions of the papers have gone through a new review process by at least three reviewers.This special issue starts with two articles on analyzing and learning from multimodal signals to inform human behavior.In "AttentiveVideo: A Multimodal Approach to Quantify Emotional Responses to Mobile Advertisements," the authors propose AttentiveVideo, a scalable intelligent mobile interface with corresponding inference algorithms to monitor and quantify the effects of mobile video advertising in real time.This interface employs a combination of implicit photoplethysmography sensing and facial expression analysis to detect attention, engagement, and sentiment of viewers as they watch video advertisements on unmodified smartphones.In "Wearables and Social Signal Processing for Better Public Presentations," the authors studied

Point clouds are one of the most promising technologies for 3D content representation. In this paper, we describe a study on quality assessment of point clouds, degraded by octree-based compression on different levels. The test contents were displayed using Screened Poisson surface reconstruction, without including any textural information, and they were rated by subjects in a passive way, using a 2D image sequence. Subjective evaluations were performed in five independent laboratories in different countries, with the inter-laboratory correlation analysis showing no statistical differences, despite the different equipment employed. Benchmarking results reveal that the state-of-the-art point cloud objective metrics are not able to accurately predict the expected visual quality of such test contents. Moreover, the subjective scores collected from this experiment were found to be poorly correlated with subjective scores obtained from another test involving visualization of raw point clouds. These results suggest the need for further investigations on adequate point cloud representations and objective Quality assessment tools.

People with disabilities frequently use the Internet to perform a variety of common activities; however, they may often encounter aggravated accessibility barriers when using mobile devices to access the Web. In order to alleviate the problems faced by this group when using mobile devices, we have extended a previously developed transcoding-based system that adapts non-accessible web pages to the needs of specific users in order to enhance their accessibility. In this version, we included new adaptation techniques gathered from the literature in order to apply transcoding techniques to mobile devices. The enhanced system was evaluated with eight users with reduced mobility using tablets. The exploratory study suggests that alternative interaction methods such as the ones named ‘end tap’ and ‘steady tap’ are beneficial for some participants with reduced mobility, dexterity or strength in the upper limbs. Other results show that six of the eight users preferred the adapted version with enlarged interaction elements which required less physical effort, even if this adaptation increases the size of the page with the disadvantages associated with such a change.

On-body interaction techniques are gaining traction, and opening up new avenues to control interactive systems. At the same time, they reveal potential to increase the accessibility of systems like touch based smartphones and other mobile devices for visually impaired users. However, for this potential to be realised, it is paramount that these techniques can be used in a multitude of contextual settings, and, ideally, do not impose training and calibration procedures. Our approach intends to optimize signal filtering, feature extraction parameters and classifier configurations for each defined gesture. The results show a 98.35% accuracy for the optimized classifier. We proceeded to conduct a validation study (15 participants) in three contexts: seated, standing and walking. Our findings show that, despite the gesture being trained by someone not participating in the study, the average accuracy was 94.67%. We also concluded that, while walking, false positives can impact its usefulness.

Interactive surfaces, gesture recognition, object tracking, tangible interaction are increasingly moving from the research arena to the domain of commercial applications. However, the effort required to combine all these technologies is still a barrier preventing a wider adoption. In this paper, we present TACTIC, an API combining touch surfaces, tangibles, and the interaction space above the surface, in a way that allows developers to easily combine all these features, and distribute interfaces across multiple devices if required. Additionally, we present the results of a developer study showing how TACTIC is easy to learn and use.

The current development of interactive systems is shifting its focus into adding new features and capabilities, encompassing for example, new input devices and ways of interacting. Some applications make use of different modalities for both input and output, which adds great complexity to such systems. Due to a possible high number of input modalities and devices available, the task of combining all the information conveyed by users from these sources, becomes critical and troublesome. This process is commonly referred to, as multi modal fusion, and is performed by fusion engines, components of multi modal systems, that have the purpose of receiving multiple streams of input, combine them, and reaching an interpretation of user intent. Evaluating the efficiency of this process is a task that requires a considerate amount of effort, due to all the variables involved. In this paper we present an evaluation framework and methodology aimed towards the assessment and optimization of fusion engines performance. We begin by correlating our work to project GUIDE, explaining how fusion is achieved and how information about user and context are used for adaptation. Subsequent sections discuss the proposed framework, and how it enables developers to assess and improve their components performance. The article concludes by showing some results that demonstrate the benefits of using such an approach and the impact it can have on the development of fusion engines.

This workshop aims to gap the bridge between mainstream research on intelligent systems and accessibility researchers by presenting papers and demonstrations on developing adaptable multimodal systems for elderly and disabled users. The workshop is organized in the context of EU GUIDE project and focus on Web and Digital TV applications. However the research and applications are relevant for different platforms like computers, tablet and ubiquitous devices. The workshop consists of a keynote speech on standardization of developing intelligent and accessible system followed by five paper and demonstration presentations. A set of papers from this workshop will later appear at the International Journal of Digital Television.

The development of TV applications nowadays excludes users with certain impairments from interacting with and accessing the same type of contents as other users do. Developers are also not interested in developing new or different versions of applications targeting different user characteristics. In this paper we describe a novel adaptive accessibility approach on how to develop accessible TV applications, without requiring too much additional effort from the developers. Integrating multimodal interaction, adaptation techniques and the use of simulators in the design process, we show how to adapt User Interfaces to the individual needs and limitations of elderly users. For this, we rely on the identification of the most relevant impairment configurations among users in practical user-trials, and we draw a relation with user specific characteristics. We provide guidelines for more accessible and centered TV application development.

Digital Talking Books (DTBs) offer to visually impaired users an evolution of analogue talking books that mimics the interaction possibilities of print books. This paper describes a new DTB player which tries to improve the usability and accessibility of current players, through the combination of the possibilities offered by multimodal interaction and interface adaptability, and the integration of several language processing components. Besides the potential for a greater enjoyment of the reader in general, these modifications also pave the way to the use of DTBs in different domains, from e-inclusion to e-learning applications. Index Terms: digital talking books, Portuguese. 1.

This article presents FAME, a model-based Framework for Adaptive Multimodal Environments. FAME proposes an architecture for adaptive multimodal applications, a new way to represent adaptation rules - the behavioral matrix - and a set of guidelines to assist the design process of adaptive multimodal applications. To demonstrate FAME's validity, the development process of an adaptive Digital Talking Book player is summarized.

We present DiTaBBu, Digital Talking Books Builder, a framework for automatic production of time-based hypermedia for the Web, focusing on the Digital Talking Books domain. Delivering Digital Talking Books collections to a wide range of users is an expensive task, as it must take into account each user profile's different needs, therefore authoring should be dismissed in favour of automation. With DiTaBBu, we enable automated content delivery in several playback platforms, targeted to specific user needs, featuring powerful navigation capabilities over the content. DiTaBBu can also be used as testbed for prototyping novel capabilities, through its flexible extension mechanisms.

In this paper we identify adaptation enabling variables, and components that can be adapted, in a setting specific to Digital Talking Books. We then propose an evolution to our Digital Talking Book builder framework, to enable the production of adaptive books.