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University of Cambridge > Talks.cam > Inference Group > Shape writing: fluid text entry on mobile devices
Shape writing: fluid text entry on mobile devicesAdd to your list(s) Download to your calendar using vCal
If you have a question about this talk, please contact David MacKay. Mobile devices gain increasing computational power and storage capabilities, and there are already mobile phones that can show movies, act as digital music players and offer full-scale web browsing. The bottleneck for information flow is however limited by the inefficient communication channel between the user and the small device. The small mobile phone form factor has proven to be surprisingly difficult to overcome and limited text entry capabilities are in effect crippling mobile devices’ use experience. The desktop keyboard is too large for mobile phones, and the keypad too limited. In recent years, advanced mobile phones have come equipped with touch-screens that enable new text entry solutions. In this talk I will report on how we explored how software keyboards on touch-screens can be improved to provide an efficient and practical text entry experience on mobile devices. The central hypothesis is that it is possible to combine three elements: software keyboard, language redundancy and pattern recognition, and create a new effective text entry interface. Words form shapes on the software keyboard layout. Users write words by articulating the shapes for words on the software keyboard. Experimental results show that novice users can write text with an average entry rate of 25 wpm and an error rate of 1% after 35 minutes of practice. An accelerated novice learning experiment shows that users can exactly copy a single well-practiced phrase with an average entry rate of 46.5 wpm, with individual phrase entry rate measurements up to 99 wpm. Taken together, the quantitative results show that shape writing is among the fastest mobile text entry interfaces, both initially and after practice, that are currently known. This is joint work with Dr. Shumin Zhai. This work was carried out at IBM Almaden Research Center and Linköping University. This talk is part of the Inference Group series. This talk is included in these lists:
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