Word predictions in a text entry interface can help accelerate a user’s input. This may especially be true for users who have a slow input rate due to some form of motor-impairment. The choice of how many word predictions to offer in a text entry interface is an important design decision. In this work, we offered different number of word predictions in a keyboard where able-bodied users had to dwell on a key for one second to click it. We found participants’ text entry rate did not improve with increasing number of predictions.
more »
« less
FlexType: Flexible Text Input with a Small Set of Input Gestures
In many situations, it may be impractical or impossible to enter text
by selecting precise locations on a physical or touchscreen keyboard.
We present an ambiguous keyboard with four character groups that
has potential applications for eyes-free text entry, as well as text entry
using a single switch or a brain-computer interface.We develop
a procedure for optimizing these character groupings based on a disambiguation
algorithm that leverages a long-span language model.
We produce both alphabetically-constrained and unconstrained
character groups in an offline optimization experiment and compare
them in a longitudinal user study. Our results did not show a
significant difference between the constrained and unconstrained
character groups after four hours of practice. As expected, participants
had significantly more errors with the unconstrained groups
in the first session, suggesting a higher barrier to learning the
technique.We therefore recommend the alphabetically-constrained
character groups, where participants were able to achieve an average
entry rate of 12.0 words per minute with a 2.03% character
error rate using a single hand and with no visual feedback.
more »
« less
- Award ID(s):
- 1909248
- NSF-PAR ID:
- 10403998
- Date Published:
- Journal Name:
- Proceedings of the 28th International Conference on Intelligent User Interfaces
- Page Range / eLocation ID:
- 584 to 594
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Typing on a midair keyboard in mixed reality can be difficult due to the lack of tactile feedback when virtual keys are tapped. Locating the keyboard over a real-world surface offers a potential way to mitigate this issue. We measured user performance and preference when a virtual keyboard was located on a table, on a wall, or in midair. Despite the additional tactile feedback offered by the table and wall locations, we found the midair location had a significantly higher entry rate with a similar error rate compared to the other locations. Participants also preferred the midair location over the other locations.more » « less
-
null (Ed.)Typing every character in a text message may require more time or effort than strictly necessary. Skipping spaces or other characters may be able to speed input and also reduce a user's physical input effort. This can be particularly important for people with motor impairments. In a large crowdsourced study, we found workers frequently abbreviated text by omitting mid-word vowels. We designed a recognizer optimized for noisy input where users often omit spaces and mid-word vowels. We show using neural language models for selecting training text and rescoring sentences improved accuracy. On noisy touchscreen data collected from hundreds of users, we found accurate abbreviated input was possible even if a third of characters were omitted. Finally, in a study where users had to dwell for a second on each key, sentence abbreviated input was competitive with a conventional keyboard with word predictions. After practice, users wrote abbreviated sentences at 9.6 words-per-minute versus word input at 9.9 words-per-minute.more » « less
-
In various scenarios from system login to writing emails, documents, and forms, keyboard inputs carry alluring data such as passwords, addresses, and IDs. Due to commonly existing non-alphabetic inputs, punctuation, and typos, users' natural inputs rarely contain only constrained, purely alphabetic keys/words. This work studies how to reveal unconstrained keyboard inputs using auditory interfaces. Audio interfaces are not intended to have the capability of light sensors such as cameras to identify compactly located keys. Our analysis shows that effectively distinguishing the keys can require a fine localization precision level of keystroke sounds close to the range of microseconds. This work (1) explores the limits of audio interfaces to distinguish keystrokes, (2) proposes a μs-level customized signal processing and analysis-based keystroke tracking approach that takes into account the mechanical physics and imperfect measuring of keystroke sounds, (3) develops the first acoustic side-channel attack study on unconstrained keyboard inputs that are not purely alphabetic keys/words and do not necessarily follow known sequences in a given dictionary or training dataset, and (4) reveals the threats of non-line-of-sight keystroke sound tracking. Our results indicate that, without relying on vision sensors, attacks using limited-resolution audio interfaces can reveal unconstrained inputs from the keyboard with a fairly sharp and bendable "auditory eyesight."more » « less
-
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.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1145/3581641.3584077
