KeySense: 基于LLM的双手下十指触屏输入
KeySense: LLM-Powered Hands-Down, Ten-Finger Typing on Commodity Touchscreens
AI总结：
KeySense通过认知-运动时间模式和微调LLM解码器，实现高效的十指触屏输入，无需额外硬件。
摘要：
现有的触屏软件键盘阻止用户将手放在上面，迫使用户以缓慢且疲劳的食指点击方式（
英文摘要：
Existing touchscreen software keyboards prevent users from resting 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 using cognitive-motor timing patterns, and then uses a fine-tuned LLM decoder to convert the resulting noisy letter sequence into the intended word. In controlled component tests, the decoder substantially outperforms two 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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
