Most existing speech activity trackers used in human subject studies are bulky, record raw audio content which invades participant privacy, have complicated hardware and non-customizable software, and are too expensive for large-scale deployment. The present effort seeks to overcome these challenges by proposing the TILES Audio Recorder (TAR) - an unobtrusive and scalable solution to track audio activity using an affordable miniature mobile device with an open-source app. For this recorder, we make use of Jelly Pro Mobile, a pocket-sized Android smartphone, and employ two open-source toolkits: openSMILE and Tarsos-DSP. Tarsos-DSP provides a Voice Activity Detection capability that triggers openSMILE to extract and save audio features only when the subject is speaking. Experiments show that performing feature extraction only during speech segments greatly increases battery life, enabling the subject to wear the recorder up to 10 hours at time. Furthermore, recording experiments with ground-truth clean speech show minimal distortion of the recorded features, as measured by root mean-square error and cosine distance. The TAR app further provides subjects with a simple user interface that allows them to both pause feature extraction at any time and also easily upload data to a remote server.