LLM Powered Text Entry Decoding and Flexible Typing on Smartphones
Yan Ma, Dan Zhang, I. V. Ramakrishnan, Xiaojun Bi · 2025
decoder, and 95.4% on real-word tap typing data. In particular, our decoder supports Flexible Typing, allowing users to enter a word with taps, gestures, multi-stroke gestures, and tap-gesture combinations. User study results show that Flexible Typing is beneficial and well-received by participants, where 35.9% of words were entered using word gestures, 29.0% with taps, 6.1% with multi-stroke gestures, and the remaining 29.0% using tap-gestures. Our investigation suggests that the LLM-based decoder improves decoding accuracy over existing word gesture decoders while enabling the Flexible Typing method, which enhances the overall typing experience and accommodates diverse user preferences.