Abstract
Since the keyboard is the most common method for text input on computers today, the design of the keyboard layout is very significant. Despite the fact that the QWERTY keyboard layout was designed more than 100 years ago, it is still the predominant layout in use today. There have been several attempts to design better layouts, both manually and automatically. In this paper we improve on previous works on automatic keyboard layout optimization, by using a deep neural network to assist in a genetic search algorithm, which enables the use of a sophisticated keyboard evaluation function that would otherwise take a prohibitive amount of time. We also show that a better choice of crossover routine greatly improves the genetic search. Finally, in order to test how users with different levels of experience adapt to new keyboard layouts, we conduct some layout adaptation experiments with 300 participants to examine how users adapt to new keyboard layouts.
Original language | English |
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Article number | 2360002 |
Journal | International Journal on Artificial Intelligence Tools |
Volume | 32 |
Issue number | 5 |
DOIs | |
State | Published - 1 Aug 2023 |
Keywords
- Keyboard layout
- genetic algorithm
- neural network
All Science Journal Classification (ASJC) codes
- Artificial Intelligence