Understanding the Behavior Transparency of Voice Assistant Applications Using the ChatterBox Framework

Abstract

A voice assistant (VA) is a platform that provides users with a wide range of services via interaction with a voice application using verbal commands. Since the VA application is deployed in the cloud, its behavior is not transparent to the user, which raises privacy concerns. In this study, we developed a framework called ChatterBox, which attempts to analyze VA applications via extensive continuous interaction, to understand their behavior. ChatterBox is capable of parsing and generating dialogues by utilizing natural language processing approach. It can also parse application-level messages to understand how a VA app acquires personal information. ChatterBox supports English and Japanese, which are completely different languages, and can extract more than twice as many dialogues from VA applications compared to SkillExplorer, a state-of-the-art VA dialogue analysis system. Based on analyses of English and Japanese VA applications using ChatterBox, we revealed that 5-15% of VA applications collect personal information or recorded user identifiers in a non-transparent manner, and 76-94% applications collected personal information without providing appropriate privacy policies. In light of these findings, we discuss the implementation of a highly transparent VA application platform.