Abstract | ||
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ABSTRACT Decoding on phrase-level may afford more correction accuracy than on word-level according to previous research. However, how phrase-level input affects the user typing behavior, and how to design the interaction to make it practical remain under explored. We present PhraseFlow, a phrase-level input keyboard that is able to correct previous text based on the subsequently input sequences. Computational studies show that phrase-level input reduces the error rate of autocorrection by over 16%. We found that phrase-level input introduced extra cognitive load to the user that hindered their performance. Through an iterative design-implement-research process, we optimized the design of PhraseFlow that alleviated the cognitive load. An in-lab study shows that users could adopt PhraseFlow quickly, resulting in 19% fewer error without losing speed. In real-life settings, we conducted a six-day deployment study with 42 participants, showing that 78.6% of the users would like to have the phrase-level input feature in future keyboards. |
Year | DOI | Venue |
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2021 | 10.1145/3411764.3445166 | Conference on Human Factors in Computing Systems |
Keywords | DocType | Citations |
Text entry, autocorrection, phrase-level input, keyboard | Conference | 0 |
PageRank | References | Authors |
0.34 | 0 | 2 |
Name | Order | Citations | PageRank |
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Mingrui Ray Zhang | 1 | 0 | 3.04 |
Shumin Zhai | 2 | 4106 | 400.66 |