Low Complexity NLMS for Multiple Loudspeaker Acoustic ECHO Canceller Using Relative Loudspeaker Transfer Functions

Ofer Schwartz, Emanuel A.P. Habets, Sharon Gannot

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Speech signals captured by a microphone mounted to a smart soundbar or speaker are inherently contaminated by echos. Modern smart devices are usually characterized by low computational capabilities and low memory resources; in these cases, a low-complexity acoustic echo canceller (AEC) may be preferred even though a tolerable degradation in the cancellation occurs. In principle, devices with multiple loudspeakers need an individual AEC for each loudspeaker because the transfer function (TF) from each loudspeaker to the microphone must be estimated. In this paper, we present an normalized least mean square (NLMS) algorithm for a multi-loudspeaker case using relative loudspeaker transfer functions (RLTFs). In each iteration, the RLTFs between each loudspeaker and the reference loudspeaker are estimated first, and then the primary TF between the reference loudspeaker and the microphone. Assuming loudspeakers that are close to each other, the RLTFs can be estimated using fewer coefficients w.r.t. the primary TF, yielding a reduction of 3:4 in computational complexity and 1:2 in memory usage. The algorithm is evaluated using both simulated and real room impulse responses (RIRs) of two loudspeakers with a reverberation time set to 0.3 s and several distances between the loudspeakers.

Original languageEnglish
Title of host publication2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages446-450
Number of pages5
ISBN (Electronic)9781509066315
DOIs
StatePublished - May 2020
Event2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020 - Barcelona, Spain
Duration: 4 May 20208 May 2020

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume2020-May
ISSN (Print)1520-6149

Conference

Conference2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020
Country/TerritorySpain
CityBarcelona
Period4/05/208/05/20

Bibliographical note

Publisher Copyright:
© 2020 IEEE.

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