TY - JOUR
T1 - Keyboard Layout Optimization and Adaptation
AU - Nivasch, Keren
AU - Azaria, Amos
N1 - Publisher Copyright:
© 2023 World Scientific Publishing Company.
PY - 2023/8/1
Y1 - 2023/8/1
N2 - 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.
AB - 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.
KW - Keyboard layout
KW - genetic algorithm
KW - neural network
UR - http://www.scopus.com/inward/record.url?scp=85169437198&partnerID=8YFLogxK
U2 - 10.1142/S0218213023600023
DO - 10.1142/S0218213023600023
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AN - SCOPUS:85169437198
SN - 0218-2130
VL - 32
JO - International Journal on Artificial Intelligence Tools
JF - International Journal on Artificial Intelligence Tools
IS - 5
M1 - 2360002
ER -