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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Ren, X. |
| Copyright Year | 2005 |
| Description | Author affiliation: Dept. of Inf. Syst. Eng., Kochi Univ. of Technol. (Ren, X.) |
| Abstract | This paper presents two experiments to determine the optimal size of a box for the input of Chinese characters (called "Kanji" in Japanese) mixed with Japanese Kana (phonetic) handwriting characters on a tablet computer. The experiments involve an evaluation of boxes of different sizes. The results are assessed in terms of high performance factors (e.g., high character recognition rates, minimal stroke protrusions outside the character box) and subjective ratings (e.g., ease of writing and a minimum level of fatigue). The results show that the optimal size of character boxes for Kanji & Kana characters is around 1.44 times 1.44 cm. The experimental results also show that the optimal size is the same for both PDAs and Tablet PCs. The results provide important guidelines to designers who are concerned about the interplay between user comfort, input efficiency and output display efficiency. The knowledge obtained from our experiments on Tablet PCs would be added to the literature on optimal size for handwriting character entry boxes |
| Sponsorship | Univ. of Aizu, Japan Nat. Natural Sci. Found. China Fudan GrandHorizon Inf. Technol., Inc. China Hewlett-Packard Co., Ltd |
| Starting Page | 548 |
| Ending Page | 552 |
| File Size | 169706 |
| Page Count | 5 |
| File Format | |
| ISBN | 076952432X |
| DOI | 10.1109/CIT.2005.97 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2005-09-21 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Natural languages Writing User interfaces Fatigue Displays Error correction Character recognition Personal communication networks Personal digital assistants Information systems |
| Content Type | Text |
| Resource Type | Article |
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