[CHI'26] KeySense: LLM-Powered Hands-Down, Ten-Finger Typing on Commodity Touchscreens

Tony Li, Yan Ma, Zhuojun Li, Chun Yu, IV Ramakrishnan, Xiaojun Bi

Posted by CaveSpider on April 13, 2026

Paper Abstract

Existing touchscreen software keyboards prevent users from rest-ing their hands, forcing slow and fatiguing index-finger tapping (“chicken typing”) instead of familiar hands-down ten-finger typing. We present KeySense, a purely software solution that preserves physical keyboard motor skills. KeySense isolates intentional taps from resting-finger noise with cognitive–motor timing patterns, and then uses a fine-tuned LLM decoder to turn the resulting noisy letter sequence into the intended word. In controlled component tests, this decoder substantially outperforms 2 statistical baselines (top-1 accuracy 84.8% vs 75.7% and 79.3%). A 12-participant study shows clear ergonomic and performance benefits: compared with the conventional hover-style keyboard, users rated KeySense as markedly less physically demanding (NASA-TLX median 1.5 vs 4.0), and after brief practice, typed significantly faster (WPM 28.3 vs 26.2, p <0.01). These results indicate that KeySense enables accurate, efficient and comfortable ten-finger text entry on commodity touchscreens, without any extra hardware.

[Paper] [DOI]