Acoustic echoes reveal room shape

Ivan Dokmani, Reza Parhizkar, Andreas Walther, Yue M. Lu, Martin Vetterli

Research output: Contribution to journalArticlepeer-review

Abstract

Imagine that you are blindfolded inside an unknown room. You snap your fingers and listen to the room's response. Can you hear the shape of the room? Some people can do it naturally, but can we design computer algorithms that hear rooms? We show how to compute the shape of a convex polyhedral room from its response to a known sound, recorded by a few microphones. Geometric relationships between the arrival times of echoes enable us to "blindfoldedly" estimate the room geometry. This is achieved by exploiting the properties of Euclidean distance matrices. Furthermore, we show that under mild conditions, first-order echoes provide a unique description of convex polyhedral rooms. Our algorithm starts from the recorded impulse responses and proceeds by learning the correct assignment of echoes to walls. In contrast to earlier methods, the proposed algorithm reconstructs the full 3D geometry of the room from a single sound emission, and with an arbitrary geometry of the microphone array. As long as the microphones can hear the echoes, we can position them as we want. Besides answering a basic question about the inverse problem of room acoustics, our results find applications in areas such as architectural acoustics, indoor localization, virtual reality, and audio forensics.

Original languageEnglish (US)
Pages (from-to)12186-12191
Number of pages6
JournalProceedings of the National Academy of Sciences of the United States of America
Volume110
Issue number30
DOIs
StatePublished - Jul 23 2013
Externally publishedYes

Keywords

  • Echo sorting
  • Geometry reconstruction
  • Image sources
  • Room geometry

ASJC Scopus subject areas

  • General

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