Enhanced stroke-based Chinese input methods for mobile devices


Student thesis: Master's Thesis

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  • Chi Kwan WONG

Related Research Unit(s)


Awarding Institution
Award date15 Jul 2011


During the last three and half decades, thousands of Chinese input methods for computing devices have been developed. Nevertheless, people are still looking for better Chinese input methods in terms of ease of use and memorization, high input speed and improved virtual keyboard implementation on mobile devices. The conventional well-known stroke-based Chinese input method using only five basic stroke types could achieve low learning curve and small keypad implementation, but its input speed is limited by the complexity of Chinese characters. To tackle this problem, simplified character and phrase encoding methods using (3+3) rules are proposed in this study. It is called G6 (diG-6). G6 only takes the first 3 strokes and the last 3 strokes of a character to enhance the performance of conventional stroke-based Chinese input methods. To further enhance the input speed, phrases are encoded with the first 3 strokes of the first character and the first 3 strokes of the last character of the phrases. Experimental results show that the G6 can improve ALIC (Average Length of Input Codes), HRFC (Hit Rate of First Character) and KSPC (Key Strokes Per Character) as compared with conventional T9 stroke-based Chinese input method. G6 has successfully implemented on MS-Windows, Apple OSX and Google Android platforms using QWERTY keyboard and virtual keypad. With the advancements of the electronic technology, inputting Chinese on mobile devices, especially touchscreen smartphones, become accustomed. Due to the popularity of touchscreen devices, the physical keyboards are being replaced by finger-operated virtual keyboards. With more devices using virtual keyboard, conventional Chinese input methods became adoptable for mobile devices. Most of the conventional Chinese input methods, however, are designed for QWERTY keyboard. The limited screen size of mobile devices incurs the input keys become tiny. It causes relatively high typo error rate that requires additional keystrokes to fix the errors. With the advancement of touchscreen technology, texting on touchscreen devices is no longer limited by finger tapping; it can also be performed by finger gestures. In this study, two novel dynamic keypad designs using finger gestures for character or radical selections are proposed to enhance the characters searching and input speed of the stroke-based Chinese input on touchscreen smartphones. The first approach is called DCK (Dynamic Candidate Keypad), in which eight frequently used Chinese characters are dynamically displayed on each of five stroke keys. These character candidates are changing with the input strokes and these characters can be directly selected by one of eight unidirectional finger gestures. Experimental results show that the proposed DCK can significantly enhance the top most 600 frequently used Chinese characters searching and input using stroke-based input method. The second approach, instead of candidate character selection, it applies dynamic keypad design for radical-stroke (RS) based Chinese character input using a dynamic radical keypad (DRK). In which commonly used Chinese radicals are dynamically displayed on the stroke keys of the DRK and similarly these radicals can be selected by unidirectional finger gestures. With the use of this new RS-DRK design, lot of radicals can be displayed and selected with a finger gesture motion and a few taps. It improves the input speed of complex Chinese characters that start or end with frequently used radicals. Experimental results demonstrated that RS-DRK could improve the KSPC, Total Error Rate and Character Per Minute for inexperienced and experienced users of RS-DRK as compared with conventional stroke-based Chinese input method.

    Research areas

  • Data processing, Chinese characters, Mobile computing