531 research outputs found
Inviscid text entry and beyond
The primary focus of our workshop is on exploring ways to enable inviscid text entry on mobile devices. In inviscid text entry, it is the user's creativity that is the text-creation bottleneck rather than the text entry interface. The inviscid rate is estimated at 67 wpm while current mobile text entry methods are typically 20-40 wpm. In this workshop, participants will discuss and demonstrate early work into novel methods that allow very rapid text entry, even if such methods currently are quite error-prone. In addition to submitting a position paper, participants are strongly encouraged to bring a demo to present during the workshop's interactive Show-and-Tell session. As well as exploring new entry methods, the workshop will discuss experimental tasks and evaluation methodologies for researching inviscid text entry. Looking beyond the speed of entry, the workshop will explore often overlooked aspects of text entry such as user adaptation, post-entry correction/revision/formatting, entry of diverse types of text, and entry when a user's input or output capabilities are limited. Finally, the workshop serves to strengthen the community of text entry researchers who attend CHI, as well as provide an opportunity for new members to join this community
Velocitap: Investigating fast mobile text entry using sentence-based decoding of touchscreen keyboard input
We present VelociTap: a state-of-the-art touchscreen keyboard
decoder that supports a sentence-based text entry approach.
VelociTap enables users to seamlessly choose from
three word-delimiter actions: pushing a space key, swiping
to the right, or simply omitting the space key and letting the
decoder infer spaces automatically. We demonstrate that VelociTap
has a significantly lower error rate than Google’s keyboard
while retaining the same entry rate. We show that intermediate
visual feedback does not significantly affect entry
or error rates and we find that using the space key results
in the most accurate results. We also demonstrate that enabling
flexible word-delimiter options does not incur an error
rate penalty. Finally, we investigate how small we can make
the keyboard when using VelociTap. We show that novice
users can reach a mean entry rate of 41 wpm on a 40mm wide
smartwatch-sized keyboard at a 3% character error rate.This is the accepted manuscript. The final version is available from ACM at http://dl.acm.org/citation.cfm?id=2702135
Investigating error injection to enhance the effectiveness of mobile text entry studies of error behaviour
During lab studies of text entry methods it is typical to observer very few errors in participants' typing - users tend to type very carefully in labs. This is a problem when investigating methods to support error awareness or correction as support mechanisms are not tested. We designed a novel evaluation method based around injection of errors into the users' typing stream and report two user studies on the effectiveness of this technique. Injection allowed us to observe a larger number of instances and more diverse types of error correction behaviour than would normally be possible in a single study, without having a significant impact on key input behaviour characteristics. Qualitative feedback from both studies suggests that our injection algorithm was successful in creating errors that appeared realistic to participants. The use of error injection shows promise for the investigation of error correction behaviour in text entry studies
The Impact of Word, Multiple Word, and Sentence Input on Virtual Keyboard Decoding Performance
Entering text on non-desktop computing devices is often done
via an onscreen virtual keyboard. Input on such keyboards
normally consists of a sequence of noisy tap events that specify
some amount of text, most commonly a single word. But
is single word-at-a-time entry the best choice? This paper
compares user performance and recognition accuracy of wordat-
a-time, phrase-at-a-time, and sentence-at-a-time text entry
on a smartwatch keyboard. We evaluate the impact of differing
amounts of input in both text copy and free composition tasks.
We found providing input of an entire sentence significantly
improved entry rates from 26wpm to 32wpm while keeping
character error rates below 4%. In offline experiments with
more processing power and memory, sentence input was recognized
with a much lower 2.0% error rate. Our findings suggest
virtual keyboards can enhance performance by encouraging
users to provide more input per recognition event.This work was supported by Google Faculty awards (K.V. and
P.O.K.
Comparing Smartphone Speech Recognition and Touchscreen Typing for Composition and Transcription
International audienceRuan et al. found transcribing short phrases with speech recognition nearly 200% faster than typing on a smartphone. We extend this comparison to a novel composition task, using a protocol that enables a controlled comparison with transcription. Results show that both composing and transcribing with speech is faster than typing. But, the magnitude of this difference is lower with composition, and speech has a lower error rate than keyboard during composition, but not during transcription. When transcribing, speech outperformed typing in most NASA-TLX measures, but when composing, there were no significant differences between typing and speech for any measure except physical demand
Comparing Smartphone Speech Recognition and Touchscreen Typing for Composition and Transcription
Ruan et al. found transcribing short phrases with speech recognition nearly 200% faster than typing on a smartphone. We extend this comparison to a novel composition task, using a protocol that enables a controlled comparison with transcription. Results show that both composing and transcribing with speech is faster than typing. But, the magnitude of this difference is lower with composition, and speech has a lower error rate than keyboard during composition, but not during transcription. When transcribing, speech outperformed typing in most NASA-TLX measures, but when composing, there were no significant differences between typing and speech for any measure except physical demand
WiseType : a tablet keyboard with color-coded visualization and various editing options for error correction
To address the problem of improving text entry accuracy in mobile devices, we present a new tablet keyboard that offers both immediate and delayed feedback on language quality through auto-correction, prediction, and grammar checking. We combine different visual representations for grammar and spelling errors, accepted predictions, and auto-corrections, and also support interactive swiping/tapping features and improved interaction with previous errors, predictions, and auto-corrections. Additionally, we added smart error correction features to the system to decrease the overhead of correcting errors and to decrease the number of operations. We designed our new input method with an iterative user-centered approach through multiple pilots. We conducted a lab-based study with a refined experimental methodology and found that WiseType outperforms a standard keyboard in terms of text entry speed and error rate. The study shows that color-coded text background highlighting and underlining of potential mistakes in combination with fast correction methods can improve both writing speed and accuracy
DoubleType: A wearable double bracelet concept for text entry
Wearable devices are used for text entry on a daily basis. Nowadays, people use their fingers to type text on touchscreens. Unfortunately, the screen size is too small to be able to type text for a longer period of time comfortably compared to quick tasks, such as checking social media posts or email.
I present DoubleType, a wearable solution where two bracelets are used together to type text. When used together, the combined display area offers the user more screen estate for a larger software keyboard with larger keys to type and more area for the text being edited to look at. Three concepts were created and a paper prototype for each concept was produced. A video prototype was created to illustrate how the user interacts with the bracelets when entering text to the system. An online questionnaire was published and it contained images of the paper prototypes and a link to a video of the prototypes in use. 34 volunteers participated. Five background questions were asked and then five questions about the prototypes.
In general, participants did not see DoubleType as a comfortable system to use for typing text. Also, majority of participants did not think DoubleType will help avoid getting neck and shoulder pains from typing text. And, most participants would not use DoubleType to type in a standing position for some parts of one's days to avoid sitting long periods of time. Of the three concepts, participants favored the most concept C, where the concept is put on a table. From the open-ended questions it was revealed participants disliked the size of the bracelets.
There could be use of the prototype in a factory for technicians who need to make notes of the procedures they have done. Future research with working prototypes is needed to find out how ergonomic and efficient DoubleType is for text entry
Aeronautical engineering: A continuing bibliography with indexes (supplement 303)
This bibliography lists 211 reports, articles, and other documents introduced into the NASA scientific and technical information database. Subject coverage includes: design, construction, and testing of aircraft and aircraft engines; aircraft components, equipment, and systems; ground support systems; and theoretical and applied aspects of aerodynamics and general fluid dynamics
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