SoundCam: A Dataset for Finding Humans Using Room Acoustics
Authors: name: Mason Wang, name: Samuel Clarke, name: Jui-Hsien Wang, name: Ruohan Gao, name: Jiajun Wu

A room's acoustic properties are a product of the room's geometry, the
objects within the room, and their specific positions. A room's acoustic
properties can be characterized by its impulse response (RIR) between a source
and listener location, or roughly inferred from recordings of natural signals
present in the room. Variations in the positions of objects in a room can
effect measurable changes in the room's acoustic properties, as characterized
by the RIR. Existing datasets of RIRs either do not systematically vary
positions of objects in an environment, or they consist of only simulated RIRs.
We present SoundCam, the largest dataset of unique RIRs from in-the-wild rooms
publicly released to date. It includes 5,000 10-channel real-world measurements
of room impulse responses and 2,000 10-channel recordings of music in three
different rooms, including a controlled acoustic lab, an in-the-wild living
room, and a conference room, with different humans in positions throughout each
room. We show that these measurements can be used for interesting tasks, such
as detecting and identifying humans, and tracking their positions.