Poster abstract: Ubiquitous writer: Robust text input for small mobile devices via acoustic sensing

Efficient typing or text-input on mobile devices such as smart-phones and wearables is a long standing problem, due to miniature touch screen on the devices. Recently, touchscreen-free solutions leveraging on acoustic sensing have been proposed, with the advantage of low cost and ubiquitous availability. However, existing solutions usually require people to write in print-style, and more importantly they are highly vulnerable to environment change, i.e., they need repetitive training upon slight deviation of writing place or device locations. Therefore, they are far from practical usage. In this paper, we propose a novel acoustic based input system called UbiWriter, which can recognize free-style handwriting with high robustness, i.e., one time training and writing other where. UbiWriter is built on a new letter recognition principle, which treats the acoustic signal generated by letter writing on hard surfaces as a complete trajectory, and then distill recognition feature from the trajectory, which is highly resilient to environment change. For the actual realization of the principle, we adopt and synthesize multiple techniques including dynamic time wrapping based letter alignment, k-Nearest Neighbor letter classification and language structure driven word recognition. Extensive experiment results demonstrate that UbiWriter outperforms state-of-the-art under various practical settings.