Predicting text entry speed on mobile phones
Proceedings of the SIGCHI conference on Human Factors in Computing Systems
LetterWise: prefix-based disambiguation for mobile text input
Proceedings of the 14th annual ACM symposium on User interface software and technology
KSPC (Keystrokes per Character) as a Characteristic of Text Entry Techniques
Mobile HCI '02 Proceedings of the 4th International Symposium on Mobile Human-Computer Interaction
A comparison of consecutive and concurrent input text entry techniques for mobile phones
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
A comparison of two input methods for keypads on mobile devices
Proceedings of the third Nordic conference on Human-computer interaction
An enhanced multitap text entry method with predictive next-letter highlighting
CHI '05 Extended Abstracts on Human Factors in Computing Systems
LetterEase: Improving text entry on a handheld device via letter reassignment
OZCHI '05 Proceedings of the 17th Australia conference on Computer-Human Interaction: Citizens Online: Considerations for Today and the Future
Improvised layout of keypad entry system for mobile phones
Computer Standards & Interfaces
HMS: a predictive text entry method using bigrams
TextEntry '03 Proceedings of the 2003 EACL Workshop on Language Modeling for Text Entry Methods
Optimizing gaze typing for people with severe motor disabilities: the iWriter arabic interface
Proceedings of the 14th international ACM SIGACCESS conference on Computers and accessibility
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Classical mobile phone keypads which consist of 12 buttons are commonly used to write short text messages through two common methods, the multi-tap and the predictive text entry. For the Arabic language mobile keypads, all Arabic letters are distributed over the 8 buttons of the keypad where three or more letters share the same button. In this paper, a new text entry environment is proposed. The environment includes two proposed improved approaches for Arabic language messages to make the multi-tap text entry method faster and easier. The first approach is based on the idea of remapping the distribution of Arabic letters on the keypad according to the frequency of letters. In the second approach, a bi-Gram based method is used to predict the next letter to be typed automatically. The proposed approaches are evaluated using a corpus of 1514 real Arabic text messages. Several experiments were conducted to evaluate the proposed text entry environment. The results of the experiments have showed that using the proposed remapped keypad is faster and consumes less effort in comparison to the classical keypad.