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1. A Comparative Study on Single-handed Keyboards on Large-screen Mobile Devices

   https://doi.org/10.1145/3531073.3531075  

   Zhang, Kunpeng; Deng, Zhigang (June 2022, AVI 2022: Proceedings of the 2022 International Conference on Advanced Visual Interfaces)

   Bottoni, Paolo; Panizzi, Emanuele (Ed.)

   Many questions regarding single-hand text entry on modern smartphones (in particular, large-screen smartphones) remain under-explored, such as, (i) will the existing prevailing single-handed keyboards fit for large-screen smartphone users? and (ii) will individual customization improve single-handed keyboard performance? In this paper we study single-handed typing behaviors on several representative keyboards on large-screen mobile devices.We found that, (i) the user-adaptable-shape curved keyboard performs best among all the studied keyboards; (ii) users’ familiarity with the Qwerty layout plays a significant role at the beginning, but after several sessions of training, the user-adaptable curved keyboard can have the best learning curve and performs best; (iii) generally the statistical decoding algorithms via spatial and language models can well handle the input noise from single-handed typing. 

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2. A Dataset of Noisy Typing on QWERTY Keyboards

   https://doi.org/10.1145/3581754.3584174  

   Vertanen, Keith; Kristensson, Per Ola (March 2023, Companion Proceedings of the 28th International Conference on Intelligent User Interfaces)

   Text entry is a common and important part of many intelligent user interfaces. However, inferring a user’s intended text from their input can be challenging: motor actions can be imprecise, input sensors can be noisy, and situations or disabilities can hamper a user’s perception of interface feedback. Numerous prior studies have explored input on touchscreen phones, smartwatches, in midair, and on desktop keyboards. Based on these prior studies, we are releasing a large and diverse data set of noisy typing input consisting of thousands of sentences written by hundreds of users on QWERTY-layout keyboards. This paper describes the various subsets contained in this new research dataset as well as the data format. 

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3. Perceptions of Blind Adults on Non-Visual Mobile Text Entry

   https://doi.org/10.1145/3733155.3736593  

   Gaines, Dylan; Vertanen, Keith (June 2025, ACM)

   Text input on mobile devices without physical keys can be challenging for people who are blind or low-vision. We interview 12 blind adults about their experiences with current mobile text input to provide insights into what sorts of interface improvements may be the most beneficial. We identify three primary themes that were experiences or opinions shared by participants: the poor accuracy of dictation, difficulty entering text in noisy environments, and difficulty correcting errors in entered text. We also discuss an experimental non-visual text input method with each participant to solicit opinions on the method and probe their willingness to learn a novel method. We find that the largest concern was the time required to learn a new technique. We find that the majority of our participants do not use word predictions while typing but instead find it faster to finish typing words manually. Finally, we distill five future directions for non-visual text input: improved dictation, less reliance on or improved audio feedback, improved error correction, reducing the barrier to entry for new methods, and more fluid non-visual word predictions. 

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4. All in One Place: Ensuring Usable Access to Online Shopping Items for Blind Users

   https://doi.org/10.1145/3664639  

   Prakash, Yash; Nayak, Akshay Kolgar; Sunkara, Mohan; Jayarathna, Sampath; Lee, Hae-Na; Ashok, Vikas (June 2024, Proceedings of the ACM on Human-Computer Interaction)

   Perusing web data items such as shopping products is a core online user activity. To prevent information overload, the content associated with data items is typically dispersed across multiple webpage sections over multiple web pages. However, such content distribution manifests an unintended side effect of significantly increasing the interaction burden for blind users, since navigating to-and-fro between different sections in different pages is tedious and cumbersome with their screen readers. While existing works have proposed methods for the context of a single webpage, solutions enabling usable access to content distributed across multiple webpages are few and far between. In this paper, we present InstaFetch, a browser extension that dynamically generates an alternative screen reader-friendly user interface in real-time, which blind users can leverage to almost instantly access different item-related information such as description, full specification, and user reviews, all in one place, without having to tediously navigate to different sections in different webpages. Moreover, InstaFetch also supports natural language queries about any item, a feature blind users can exploit to quickly obtain desired information, thereby avoiding manually trudging through reams of text. In a study with 14 blind users, we observed that the participants needed significantly lesser time to peruse data items with InstaFetch, than with a state-of-the-art solution. 

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5. Textflow: Towards Supporting Screen-free Manipulation of Situation-Relevant Smart Messages

   https://doi.org/10.1145/3519263  

   Karimi, Pegah; Plebani, Emanuele; Martin-Hammond, Aqueasha; Bolchini, Davide (February 2022, ACM Transactions on Interactive Intelligent Systems)

   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. 

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