Preliminary Study of Adaptive Decision-Making System for Vocal Command in Smart Home

Abstract

In smart homes, prediction and decision are often defined a priori and require tuning from the user, which can be tedious, and complex. However, these smart homes have the ability to analyze the user's behavior so as to adapt their decisions automatically. We present a preliminary study that tests a voice based decision system in the home, which is modified by reinforcement learning. The system ran on a realistic corpus, which shows the interest of such an adaptation.