An online algorithm for echo cancellation, dereverberation and noise reduction based on a Kalman-EM Method

Nili Cohen, Gershon Hazan, Boaz Schwartz, Sharon Gannot

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

Many modern smart devices are equipped with a microphone array and a loudspeaker (or are able to connect to one). Acoustic echo cancellation algorithms, specifically their multi-microphone variants, are essential components in such devices. On top of acoustic echos, other commonly encountered interference sources in telecommunication systems are reverberation, which may deteriorate the desired speech quality in acoustic enclosures, specifically if the speaker distance from the array is large, and noise. Although sub-optimal, the common practice in such scenarios is to treat each problem separately. In the current contribution, we address a unified statistical model to simultaneously tackle the three problems. Specifically, we propose a recursive EM (REM) algorithm for solving echo cancellation, dereverberation and noise reduction. The proposed approach is derived in the short-time Fourier transform (STFT) domain, with time-domain filtering approximated by the convolutive transfer function (CTF) model. In the E-step, a Kalman filter is applied to estimate the near-end speaker, based on the noisy and reveberant microphone signals and the echo reference signal. In the M-step, the model parameters, including the acoustic systems, are inferred. Experiments with human speakers were carried out to examine the performance in dynamic scenarios, including a walking speaker and a moving microphone array. The results demonstrate the efficiency of the echo canceller in adverse conditions together with a significant reduction in reverberation and noise. Moreover, the tracking capabilities of the proposed algorithm were shown to outperform baseline methods.

Original languageEnglish
Article number33
JournalEurasip Journal on Audio, Speech, and Music Processing
Volume2021
Issue number1
DOIs
StatePublished - Dec 2021

Bibliographical note

Publisher Copyright:
© 2021, The Author(s).

Funding

This project has received funding from the European Union’s Horizon 2020 Research and Innovation Programme under Grant Agreement No. 871245.

FundersFunder number
Horizon 2020 Framework Programme871245

    Keywords

    • Acoustic echo cancellation
    • Array processing
    • Convolutive transfer function approximation in the STFT domain
    • Dereverberation
    • Recursive expectation-maximization algorithm

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