In this paper, we study the overhearing problem of continuous acoustic sensing devices such as Amazon Echo, Google Home, or such voice-enabled home hubs, and develop a system called SoundSifter that mitigates personal or contextual information leakage due to the presence of unwanted sound sources in the acoustic environment. Instead of proposing modifications to existing home hubs, we build an independent embedded system that connects to a home hub via its audio input. Considering the aesthetics of home hubs, we envision SoundSifter as a smart sleeve or a cover for these devices. SoundSifter has necessary hardware and software to capture the audio, isolate signals from distinct sound sources, filter out signals that are from unwanted sources, and process the signals to enforce policies such as personalization before the signals enter into an untrusted system like Amazon Echo or Google Home. We conduct empirical and real-world experiments to demonstrate that SoundSifter runs in real-time, is noise resilient, and supports selective and personalized voice commands that commercial voice-enable home hubs do not.