Text-entry aims to provide an effective and efficient pathway for humans to deliver their messages to computers. With the advent of mobile computing, the recent focus of text-entry research has moved from physical keyboards to soft keyboards. Current soft keyboards, however, increase the typo rate due to lack of tactile feedback and degrade the usability of mobile devices due to their large portion on screens. To tackle these limitations, we propose a fully imaginary keyboard (I-Keyboard) with a deep neural decoder (DND). The invisibility of I-Keyboard maximizes the usability of mobile devices and DND empowered by a deep neural architecture allows users to start typing from any position on the touch screens at any angle. To the best of our knowledge, the eyes-free ten-finger typing scenario of I-Keyboard which does not necessitate both a calibration step and a predefined region for typing is first explored in this work. For the purpose of training DND, we collected the largest user data in the process of developing I-Keyboard. We verified the performance of the proposed I-Keyboard and DND by conducting a series of comprehensive simulations and experiments under various conditions. I-Keyboard showed 18.95 and 4.06 increases in typing speed (45.57 WPM) and accuracy (95.84 ), respectively over the baseline.
For the second point, optimized text-entry supplies accessible and comfortable typing interfaces by optimizing the size, shape, and position of keys @cite_8 @cite_5 . Current optimized text-entry methods require users to learn new typing interfaces @cite_1 because knowledge transfer seldom occurs for novel typing interfaces. Furthermore, the optimization process frequently demands a calibration step. The calibration step complicates the usage of the optimized text-entries. I-Keyboard proposed in this paper does not involve learning and calibration processes since it operates with ten fingers and its decoding algorithm does not need any prior knowledge.
@cite_5 @cite_1 @cite_8
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In this paper the authors propose IPPITSU, an eyes-free, Braille-based text entry method for touch panels. In IPPITSU the user inputs a Braille cell by selecting the raised dot in it. In order to select the dots the user touches the regions corresponding to the raised dots by sliding the finger on the panel with one continuous stroke. IPPITSU is expected to be used by visually-impaired people. IPPITSU is implemented as an IME for Android devices and is available on Google Play. Current soft QWERTY keyboards often consume a large portion of the screen space on portable touchscreens. This space consumption can diminish the overall user experi-ence on these devices. In this paper, we present the 1Line keyboard, a soft QWERTY keyboard that is 140 pixels tall (in landscape mode) and 40 of the height of the native iPad QWERTY keyboard. Our keyboard condenses the three rows of keys in the normal QWERTY layout into a single line with eight keys. The sizing of the eight keys is based on users' mental layout of a QWERTY keyboard on an iPad. The system disambiguates the word the user types based on the sequence of keys pressed. The user can use flick gestures to perform backspace and enter, and tap on the bezel below the keyboard to input a space. Through an evaluation, we show that participants are able to quickly learn how to use the 1Line keyboard and type at a rate of over 30 WPM after just five 20-minute typing sessions. Using a keystroke level model, we predict the peak expert text entry rate with the 1Line keyboard to be 66--68 WPM.