Ambiguous keyboards for AAC

Purpose – “Ambiguous keyboards” and “disambiguation processes” are becoming universally recognised through the popularisation of “predictive text messaging” on mobile phones. As this paper shows, although originating in the AT and AAC fields, these terms and techniques no longer appear to be widely understood or adopted by practitioners or users. The purpose of this paper is to introduce these techniques, discussing the research and theory around them, and to suggest them as AT and AAC strategies to be considered by practitioners and users. Design/methodology/approach – This is a conceptual paper that describes the use of ambiguous keyboards and disambiguation. The hypothesis of the paper is that ambiguous keyboards and disambiguation processes offer potential to increase the efficiency and effectiveness of AAC and should thus be considered further in research and practice. Findings – The two broad methods for removing the ambiguity from the output of an ambiguous keyboard are presented. A summary of the literature around the use of disambiguation processes provided and the use of disambiguation processes for AAC discussed. Originality/value – This paper suggests that ambiguity should be adopted as a characteristic of an AAC keyboard as should the method of removing ambiguity – namely either coding or a disambiguation process

Pickup usability dominates: a brief history of mobile text entry research and adoption

Text entry on mobile devices (e.g. phones and PDAs) has been a research challenge since devices shrank below laptop size: mobile devices are simply too small to have a traditional full-size keyboard. There has been a profusion of research into text entry techniques for smaller keyboards and touch screens: some of which have become mainstream, while others have not lived up to early expectations. As the mobile phone industry moves to mainstream touch screen interaction we will review the range of input techniques for mobiles, together with evaluations that have taken place to assess their validity: from theoretical modelling through to formal usability experiments. We also report initial results on iPhone text entry speed

Investigating five key predictive text entry with combined distance and keystroke modelling

This paper investigates text entry on mobile devices using only five-keys. Primarily to support text entry on smaller devices than mobile phones, this method can also be used to maximise screen space on mobile phones. Reported combined Fitt's law and keystroke modelling predicts similar performance with bigram prediction using a five-key keypad as is currently achieved on standard mobile phones using unigram prediction. User studies reported here show similar user performance on five-key pads as found elsewhere for novice nine-key pad users

Towards high quality text entry on smartwatches

Smartwatches now provide users with access to many applications on smartphones direct from their wrists, without the need to touch their smartphone. While applications such as email, messaging, calendar and social networking provide views on the watch, there is normally no text entry method so users cannot reply on the same device. Here we introduce requirements for smartwatch text entry, an optimised alphabetic layout and present a prototype implementation together with preliminary user feedback. While raising some problems, the feedback gives indicates that reasonable quality and speed is achievable on a smartwatch and encourages our future work

Shrimp - solving collision and out of vocabulary problems in mobile predictive input with motion gesture

ABSTRACT Dictionary-based disambiguation (DBD) is a very popular solution for text entry on mobile phone keypads but suffers from two problems: 1. the resolution of encoding collision (two or more words sharing the same numeric key sequence) and 2. entering out-of-vocabulary (OOV) words. In this paper, we present SHRIMP, a system and method that addresses these two problems by integrating DBD with camera based motion sensing that enables the user to express preference through a tilting or movement gesture. SHRIMP (Small Handheld Rapid Input with Motion and Prediction) runs on camera phones equipped with a standard 12-key keypad. SHRIMP maintains the speed advantage of DBD driven predictive text input while enabling the user to overcome DBD collision and OOV problems seamlessly without even a mode switch. An initial empirical study demonstrates that SHRIMP can be learned very quickly, performed immediately faster than MultiTap and handled OOV words more efficiently than DBD

Multidimensional Pareto optimization of touchscreen keyboards for speed, familiarity and improved spell checking

The paper presents a new optimization technique for keyboard layouts based on Pareto front optimization. We used this multifactorial technique to create two new touchscreen phone keyboard layouts based on three design metrics: minimizing finger travel distance in order to maximize text entry speed, a new metric to maximize the quality of spell correction quality by minimizing neighbouring key ambiguity, and maximizing familiarity through a similarity function with the standard Qwerty layout. The paper describes the optimization process and resulting layouts for a standard trapezoid shaped keyboard and a more rectangular layout. Fitts' law modelling shows a predicted 11% improvement in entry speed without taking into account the significantly improved error correction potential and the subsequent effect on speed. In initial user tests typing speed dropped from approx. 21wpm with Qwerty to 13wpm (64%) on first use of our layout but recovered to 18wpm (85%) within four short trial sessions, and was still improving. NASA TLX forms showed no significant difference on load between Qwerty and our new layout use in the fourth session. Together we believe this shows the new layouts are faster and can be quickly adopted by users

From seen to unseen: Designing keyboard-less interfaces for text entry on the constrained screen real estate of Augmented Reality headsets

Text input is a very challenging task in the constrained screen real-estate of Augmented Reality headsets. Typical keyboards spread over multiple lines and occupy a significant portion of the screen. In this article, we explore the feasibility of single-line text entry systems for smartglasses. We first design FITE, a dynamic keyboard where the characters are positioned depending on their probability within the current input. However, the dynamic layout leads to mediocre text input and low accuracy. We then introduce HIBEY, a fixed 1-line solution that further decreases the screen real-estate usage by hiding the layout. Despite its hidden layout, HIBEY surprisingly performs much better than FITE, and achieves a mean text entry rate of 9.95 words per minute (WPM) with 96.06% accuracy, which is comparable to other state-of-the-art approaches. After 8 days, participants achieve an average of 13.19 WPM. In addition, HIBEY only occupies 13.14% of the screen real estate at the edge region, which is 62.80% smaller than the default keyboard layout on Microsoft Hololens.Peer reviewe

Designing Text Entry Methods for Non-Verbal Vocal Input

Katedra počítačové grafiky a interakc