Dimensionality Reduction of Room Acoustic Impulse Responses and Applications to System Identification

Gongping Huang, Jacob Benesty, Jingdong Chen

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

A room Acoustic Impulse Response (RAIR), which represents the sound propagation channel via direct and reflection paths from a source position to a microphone, plays a leading role in a broad range of acoustic signal processing applications, e.g., echo cancellation. In practical acoustic environments, it is not uncommon that an RAIR may consist of hundreds or even thousands of coefficients, making it challenging to identify and handle. This letter investigates the RAIR dimensionality reduction problem inspired from the concepts of dynamic mode decomposition. The objective is to find effective lower-dimensional representations of RAIRs, which are easier and more robust to identify and equalize. There are two main contributions of this work. First, we present an RAIR dimensionality reduction method. Second, we show how to apply this technique to the problem of acoustic system identification. Simulation results demonstrate that the proposed method is able to improve significantly the performance of acoustic system identification.

Original languageEnglish
Pages (from-to)1107-1111
Number of pages5
JournalIEEE Signal Processing Letters
Volume30
DOIs
StatePublished - 2023

Keywords

  • acoustic system identification
  • Dimensionality reduction
  • dynamic mode decomposition
  • room acoustic impulse response

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