Enabling Auto-Correction on Soft Braille Keyboard
Dan Zhang, Yan Ma, Glenn Dausch, William H. Seiple, Xianfeng David Gu, I. V. Ramakrishnan, Xiaojun Bi
Abstract
A soft Braille keyboard is a graphical representation of the Braille writing system on smartphones. It provides an essential text input method for visually impaired individuals, but accuracy and efficiency remain significant challenges. We present an intelligent Braille keyboard with auto-correction ability, which uses optimal transportation theory to estimate the distances between touch input and Braille patterns, and combines it with a language model to estimate the probability of entering words. The proposed system was evaluated through both simulations and user studies. In a touch interaction simulation on an Android phone and an iPhone, our intelligent Braille keyboard demonstrated superior error correction performance compared to the Android Braille keyboard with proofreading suggestions and the iPhone Braille keyboard with spelling suggestions. It reduced the error rate from 55.81% on Android and 57.13% on iPhone to 19.80% under high typing noise. Furthermore, in a user study of 12 participants who are legally blind, the intelligent Braille keyboard reduced word error rate (WER) by 59.5% (42.53% to 17.28%) with a slight drop of 0.74 words per minute (WPM), compared to a conventional Braille keyboard without auto-correction. These findings suggest that our approach has the potential to greatly improve the typing experience for Braille users on touchscreen devices.
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