VASTA: A Vision and Language-assisted Smartphone Task Automation System
Alborz Rezazadeh Sereshkeh, Gary Leung, Krish Perumal, Caleb Phillips,, Minfan Zhang, Afsaneh Fazly, Iqbal Mohomed

TL;DR
VASTA is a new system that combines vision and language understanding to enable robust, generalizable smartphone task automation through demonstration and natural language commands.
Contribution
VASTA introduces a novel integration of computer vision and natural language understanding for flexible, user-friendly smartphone automation without relying on UI structure.
Findings
Effective clustering of user utterances
Successful recognition of UI elements and automation parameters
Automates diverse smartphone tasks
Abstract
We present VASTA, a novel vision and language-assisted Programming By Demonstration (PBD) system for smartphone task automation. Development of a robust PBD automation system requires overcoming three key challenges: first, how to make a particular demonstration robust to positional and visual changes in the user interface (UI) elements; secondly, how to recognize changes in the automation parameters to make the demonstration as generalizable as possible; and thirdly, how to recognize from the user utterance what automation the user wishes to carry out. To address the first challenge, VASTA leverages state-of-the-art computer vision techniques, including object detection and optical character recognition, to accurately label interactions demonstrated by a user, without relying on the underlying UI structures. To address the second and third challenges, VASTA takes advantage of advanced…
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Taxonomy
TopicsMultimodal Machine Learning Applications · Advanced Neural Network Applications · Mobile Crowdsensing and Crowdsourcing
