Example
Consider a typical phone keypad:
Suppose a user wishes to type "The". In a traditional "multi-tap" keypad entry system, it would be necessary to do the following:
- Press 8 (tuv) once to select t.
- Press 4 (ghi) twice to select h.
- Press 3 (def) twice to select e.
Meanwhile, in a phone with predictive text, it is only necessary to:
- Press 8 once to select the (tuv) group for the first character.
- Press 4 once to select the (ghi) group for the second character.
- Press 3 once to select the (def) group for the third character.
The system updates the display as each keypress is entered to show the most probable entry. In this case, predictive text reduced the number of button presses from 5 to 3. The effect is even greater with longer, more complex words.
A dictionary-based predictive system is based on hope that the desired word is in the dictionary. That hope may be misplaced if the word differs in any way from common usage—in particular, if the word is not spelled or typed correctly, is slang, or is a proper noun. In these cases, some other mechanism must be used to enter the word.
Furthermore, the simple dictionary approach fails with agglutinative languages, where a single word doesn't necessarily represent a single semantic entity.
Read more about this topic: Predictive Text
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