Ubiquitous Writer: Robust Text Input for Small Mobile Devices via Acoustic Sensing

Efficient typing or text-input on mobile devices, such as smartphones and wearables is a long-standing problem, due to the miniature touchscreen 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 environmental change, i.e., they need repetitive training upon slight deviation of writing places or device locations. Therefore, they are far from practical usage. In this paper, we propose a novel acoustic-based text-input system called UbiWriter, which can recognize freestyle handwriting with high ubiquity, i.e., one-time training and writing elsewhere. UbiWriter is built on a new letter recognition principle, which treats the acoustic signal from writing a letter as a complete trajectory, and then distills the recognition feature that is resilient to environmental change. For the actual realization of the principle, we adopt and incorporate a series of techniques, including a feature-preserved fast letter alignment, ${K}$ -nearest neighbor letter classification, and language structure-driven word recognition. We also design and implement an APP with cloud-computing support, in order to facilitate real-time text input. Extensive experimental results demonstrate that UbiWriter outperforms the state-of-the-art under various practical settings.