This post describes our new massive distributed microphone array dataset, which is available for download from the Illinois Databank and is featured an upcoming paper at CAMSAP 2019.
The conference room used for the massive distributed array dataset.
Listening in loud noise is hard: we only have two ears, after all, but a crowded party might have dozens or even hundreds of people talking at once. Our ears are hopelessly outnumbered! Augmented listening devices, however, are not limited by physiology: they could use hundreds of microphones spread all across a room to make sense of the jumble of sounds.
Our world is already filled with microphones. There are multiple microphones in every smartphone, laptop, smart speaker, conferencing system, and hearing aid. As microphone technology and wireless networks improve, it will be possible to place hundreds of microphones throughout crowded spaces to help us hear better. Massive-scale distributed arrays are more useful than compact arrays because they are spread around and among the sound sources. One user’s listening device might have trouble distinguishing between two voices on the other side of the room, but wearable microphones on those talkers can provide excellent information about their speech signals.
Many researchers, including our team, are developing algorithms that can harness information from massive-scale arrays, but there is little publicly available data suitable for source separation and audio enhancement research at such a large scale. To facilitate this research, we have released a new dataset with 10 speech sources and 160 microphones in a large, reverberant conference room.