A keyboard app that reduces typo by half without any user notice

Smartphone keyboard encounters Deep Learning

NOTA Keyboard is a smartphone
soft keyboard that reduces typo automatically by learning users’ input patterns itself without additional manipulation or user adaptation.

Keyboard that Learns Input Patterns and Improves itself

Changing keyboard’s invisible input detecting region without user’s notice using Deep learning

Typo on soft keyboard is due to the discordance between the user’s touch input coordinate and the keyboard’s actual detecting region.

NOTA keyboard doesn’t alter the keyboard layout. Rather, it changes the invisible region of each character’s detecting region to reduce the typo gradually.

NOTA Keyboard’s Performance

Without Nota Keyboard

With Nota Keyboard

9.83%

Typo Rate

Decreased by 52.3%

4.78%

292.0 characters/min

Typing Speed

Increased by 4.8%

306.1 characters/min

9.19%

Backspace

Decreased by 23.6%

7.02%

NOTA Keyboard’s Technology for Users

Universal typo reducing technology

Typo reducing technology that can be applied to existing diverse keyboards regardless of language/input method

Personalized typo reducing technology

Reflects user’s typing habit with each individual’s hands’ shapes and positions and provide the personalized typo reducing algorithm

User friendly technology

User friendly technology that can be used instantly without any new input method or additional manipulation

Language modeling technology

Typo-reducing technology by dynamically changing key region based on the previous input characters

NOTA Team

Myungsu Chae
CEO
KAIST M.S.
Former research engineer in KAIST Institute for ITC
Former research scientist in KAIST Institute for AI
Sungsu Lim
Advisory Board
Assistant Professor of Computer Science and Engineering, Chungnam Nat’l Univ.
Ph.D. in Knowledge Service Engineering, KAIST
Hyoungkyu Song
Data Scientist
Undergraduate in Bio & Brain Engineering and School of Computing, KAIST

Junkyu Park
Data Scientist
Undergraduate in Dept. of EE, KAIST
Minkyu Yun
Data Scientist
KAIST B.S. Candidate in Computer Science
Jeongeun Ju
Manager
Seokyeong Univ. B.S.
Former staff in Kyunghee Univ.
Former staff in Kwangwoon Univ.

Partners

#3104, N28, KAIST, 291, Daehak-ro, Yuseong-gu, Daejeon, Republic of Korea

contact@nota.ai