AutoTask: Executing Arbitrary Voice Commands by Exploring and Learning from Mobile GUI
December 26, 2023 Β· Declared Dead Β· π arXiv.org
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Authors
Lihang Pan, Bowen Wang, Chun Yu, Yuxuan Chen, Xiangyu Zhang, Yuanchun Shi
arXiv ID
2312.16062
Category
cs.HC: Human-Computer Interaction
Citations
5
Venue
arXiv.org
Last Checked
4 months ago
Abstract
Voice command interfaces (VCIs) have gained increasing importance, enabling hands-free and eyes-free interaction with digital devices. However, the inherent complexity in constructing effective voice interfaces has limited the VCIs' functionalities to only a small fraction of GUI applications and tasks. This paper presents AutoTask, a VCI capable of automating any task in any mobile application without configuration or modification from developers or end users. The primary challenge for AutoTask is the lack of knowledge, as it needs to accomplish unknown tasks (e.g., user commands) within an unknown environment (e.g., GUI). To address this challenge, AutoTask employs two strategies: (1) trial and error: AutoTask explores the GUI, attempts potential operation sequences, and recovers from errors through backtracking; (2) learning from the environment: AutoTask accumulates experiences during exploration and summarizes correct knowledge from these experiences. We implemented AutoTask on Android devices and conducted an evaluation study, which proved the feasibility of AutoTask.
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