benjamin-paine/mit-impulse-response-survey

Author's Description

These are environmental Impulse Responses (IRs) measured in the real-world IR survey as described in Traer and McDermott, PNAS, 2016. The survey locations were selected by tracking the motions of 7 volunteers over the course of 2 weeks of daily life. We sent the volunteers 24 text messages every day at randomized times and asked the volunteers to respond with their location at the time the text was sent. We then retraced their steps and measured the acoustic impulse responses of as many spaces as possible. We recorded 271 IRs from a total of 301 unique locations. This data set therefore reflects the diversity of acoustic distortion our volunteers encounter in the course of daily life. All recordings were made with a 1.5 meter spacing between speaker and microphone to simulate a typical conversation.

James Traer and Josh H. McDermott, mcdermottlab.mit.edu

Repacking Notes

The following changes were made to repack for 🤗 Datasets / 🥐 Croissant:

• Mapped beggining part of filename to id.
• Mapped second part of filename to location, and turned into a class label (enumeration.)
• When present, mapped third (but not final) part of filename to detail.
• Mapped final part of filename to hits.
• Adjusted several filenames by correcting typos, homogenizing capitalization, and occasionally switching the order of location and detail.

License

These files are licensed under an MIT Creative Commons license, CC-BY 4.0. Please cite the Traer and McDermott paper when used, as exampled below.

Citation

@article{
doi:10.1073/pnas.1612524113,
author = {James Traer and Josh H. McDermott},
title = {Statistics of natural reverberation enable perceptual separation of sound and space},
journal = {Proceedings of the National Academy of Sciences},
volume = {113},
number = {48},
pages = {E7856-E7865},
year = {2016},
doi = {10.1073/pnas.1612524113},
URL = {https://www.pnas.org/doi/abs/10.1073/pnas.1612524113},
eprint = {https://www.pnas.org/doi/pdf/10.1073/pnas.1612524113},
abstract = {Sounds produced in the world reflect off surrounding surfaces on their way to our ears. Known as reverberation, these reflections distort sound but provide information about the world around us. We asked whether reverberation exhibits statistical regularities that listeners use to separate its effects from those of a sound’s source. We conducted a large-scale statistical analysis of real-world acoustics, revealing strong regularities of reverberation in natural scenes. We found that human listeners can estimate the contributions of the source and the environment from reverberant sound, but that they depend critically on whether environmental acoustics conform to the observed statistical regularities. The results suggest a separation process constrained by knowledge of environmental acoustics that is internalized over development or evolution. In everyday listening, sound reaches our ears directly from a source as well as indirectly via reflections known as reverberation. Reverberation profoundly distorts the sound from a source, yet humans can both identify sound sources and distinguish environments from the resulting sound, via mechanisms that remain unclear. The core computational challenge is that the acoustic signatures of the source and environment are combined in a single signal received by the ear. Here we ask whether our recognition of sound sources and spaces reflects an ability to separate their effects and whether any such separation is enabled by statistical regularities of real-world reverberation. To first determine whether such statistical regularities exist, we measured impulse responses (IRs) of 271 spaces sampled from the distribution encountered by humans during daily life. The sampled spaces were diverse, but their IRs were tightly constrained, exhibiting exponential decay at frequency-dependent rates: Mid frequencies reverberated longest whereas higher and lower frequencies decayed more rapidly, presumably due to absorptive properties of materials and air. To test whether humans leverage these regularities, we manipulated IR decay characteristics in simulated reverberant audio. Listeners could discriminate sound sources and environments from these signals, but their abilities degraded when reverberation characteristics deviated from those of real-world environments. Subjectively, atypical IRs were mistaken for sound sources. The results suggest the brain separates sound into contributions from the source and the environment, constrained by a prior on natural reverberation. This separation process may contribute to robust recognition while providing information about spaces around us.}}