Lune

CHI2020Top-tier venue

Using Bayes' Theorem for Command Input: Principle, Models, and Applications

Suwen Zhu, Yoonsang Kim, Jingjie Zheng, Jennifer Yi Luo, Ryan Qin, Liuping Wang, Xiangmin Fan, Feng Tian, Xiaojun Bi

2020Year
16Citations
5Top-tier citations

Abstract

Entering commands on touchscreens can be noisy, but existing interfaces commonly adopt deterministic principles for deciding targets and often result in errors. Building on prior research of using Bayes' theorem to handle uncertainty in input, this paper formalized Bayes' theorem as a generic guiding principle for deciding targets in command input (referred to as "BayesianCommand"), developed three models for estimating prior and likelihood probabilities, and carried out experiments to demonstrate the effectiveness of this formalization. More specifically, we applied BayesianCommand to improve the input accuracy of (1) point-and-click and (2) word-gesture command input. Our evaluation showed that applying BayesianCommand reduced errors compared to using deterministic principles (by over 26.9% for point-and-click and by 39.9% for word-gesture command input) or applying the principle partially (by over 28.0% and 24.5%).

Ask about this paper

Your agent reads all of it.

Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.

Questions to start from

Your agent calls

Luneget_paper_fulltext

Ask in Lune

Free to start. No credit card required.

lune papers fulltext 6ce42de0-8f66-446f-96bf-a2c59e63c4f9

Cited by top-tier papers5

Ask how each one uses it

Related papers

Dusk over the sea between two cliffs drawn in fine vertical lines