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Despite growing interest in accessible texting for people who are blind and visually impaired (BVI), little is known about the practice of texting when on the move, and especially while using assistive technologies. To address this gap, we conducted an interview-based study with 20 BVIs who text while travelling. Our findings revealed that participants engage in text outside their home in four recurrent situations: walking to a destination, waiting for public transportation, riding in a vehicle, or approaching a point of interest. Moreover, to safely send a text, participants express the need for receiving a range of information about their surroundings, including the distance to destination, upcoming obstacles, traffic jams, and weather conditions. Based on these findings, we examine three modes of situational feedback cues to integrate with messaging applications: text-based, sound effects, and tactile. Our work discusses design directions to enhance the texting experience in nomadic contexts for people who are blind and visually impaired. 

Many publicly available datasets exist that can provide factual answers to a wide range of questions that benefit the public. Indeed, datasets created by governmental and nongovernmental organizations often have a mandate to share data with the public. However, these datasets are often underutilized by knowledge workers due to the cumbersome amount of expertise and embedded implicit information needed for everyday users to access, analyze, and utilize their information. To seek solutions to this problem, this paper discusses the design of an automated process for generating questions that provide insight into a dataset. Given a relational dataset, our prototype system architecture follows a five-step process from data extraction, cleaning, pre-processing, entity recognition using deep learning, and questions formulation. Through examples of our results, we show that the questions generated by our approach are similar and, in some cases, more accurate than the ones generated by an AI engine like ChatGPT, whose question outputs while more fluent, are often not true to the facts represented in the original data. We discuss key limitations of our approach and the work to be done to bring to life a fully generalized pipeline that can take any data set and automatically provide the user with factual questions that the data can answer. 

Texting relies on screen-centric prompts designed for sighted users, still posing significant barriers to people who are blind and visually impaired (BVI). Can we re-imagine texting untethered from a visual display? In an interview study, 20 BVI adults shared situations surrounding their texting practices, recurrent topics of conversations, and challenges. Informed by these insights, we introduce TextFlow : a mixed-initiative context-aware system that generates entirely auditory message options relevant to the users’ location, activity, and time of the day. Users can browse and select suggested aural messages using finger-taps supported by an off-the-shelf finger-worn device, without having to hold or attend to a mobile screen. In an evaluative study, 10 BVI participants successfully interacted with TextFlow to browse and send messages in screen-free mode. The experiential response of the users shed light on the importance of bypassing the phone and accessing rapidly controllable messages at their fingertips while preserving privacy and accuracy with respect to speech or screen-based input. We discuss how non-visual access to proactive, contextual messaging can support the blind in a variety of daily scenarios. 

Texting relies on screen-centric prompts designed for sighted users, still posing significant barriers to people who are blind and visually impaired (BVI). Can we re-imagine texting untethered from a visual display? In an interview study, 20 BVI adults shared situations surrounding their texting practices, recurrent topics of conversations, and challenges. Informed by these insights, we introduce TextFlow: a mixed-initiative context-aware system that generates entirely auditory message options relevant to the users’ location, activity, and time of the day. Users can browse and select suggested aural messages using finger-taps supported by an off-the-shelf finger-worn device, without having to hold or attend to a mobile screen. In an evaluative study, 10 BVI participants successfully interacted with TextFlow to browse and send messages in screen-free mode. The experiential response of the users shed light on the importance of bypassing the phone and accessing rapidly controllable messages at their fingertips while preserving privacy and accuracy with respect to speech or screen-based input. We discuss how non-visual access to proactive, contextual messaging can support the blind in a variety of daily scenarios. 

Citizenry decision-making relies on data for informed actions, and official statistics provide many of the relevant data needed for these decisions. However, the wide, distributed, and diverse datasets available from official statistics remain hard to access, scrutinise and manipulate, especially for non-experts. As a result, the complexities involved in official statistical databases create barriers to broader access to these data, often rendering the data non-actionable or irrelevant for the speed at which decisions are made in social and public life. To address this problem, this paper proposes an approach to automatically generating basic, factual questions from an existing dataset of official statistics. The question generating process, now specifically instantiated for geospatial data, starts from a raw dataset and gradually builds toward formulating and presenting users with examples of questions that the dataset can answer, and for which geographic units. This approach exemplifies a novel paradigm of question-first data rendering, where questions, rather than data tables, are used as a human-centred and relevant access points to explore, manipulate, navigate and cross-link data to support decision making. This approach can automate time-consuming aspects of data transformation and facilitate broader access to data. 

Accessible onscreen keyboards require people who are blind to keep out their phone at all times to search for visual affordances they cannot see. Is it possible to re-imagine text entry without a reference screen? To explore this question, we introduce screenless keyboards as aural flows (keyflows): rapid auditory streams of Text-To-Speech (TTS) characters controllable by hand gestures. In a study, 20 screen-reader users experienced keyflows to perform initial text entry. Typing took inordinately longer than current screen-based keyboards, but most participants preferred screen-free text entry to current methods, especially for short messages on-the-go. We model navigation strategies that participants enacted to aurally browse entirely auditory keyboards and discuss their limitation and benefits for daily access. Our work points to trade-offs in user performance and user experience for situations when blind users may trade typing speed with the benefit of being untethered from the screen.