Acoustic echo cancellation

14 papers with code • 0 benchmarks • 2 datasets

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Use these libraries to find Acoustic echo cancellation models and implementations

Most implemented papers

Nonlinear Residual Echo Suppression Based on Multi-stream Conv-TasNet

Mo-yun/tasnetmi-samples 15 May 2020

Acoustic echo cannot be entirely removed by linear adaptive filters due to the nonlinear relationship between the echo and far-end signal.

ICASSP 2021 Acoustic Echo Cancellation Challenge: Datasets and Testing Framework

microsoft/AEC-Challenge 10 Sep 2020

In this challenge, we open source two large datasets to train AEC models under both single talk and double talk scenarios.

Semi-Blind Source Separation for Nonlinear Acoustic Echo Cancellation

ChengGuoliang0/audio-samples 25 Oct 2020

Unlike the commonly utilized adaptive algorithm, the proposed SBSS is based on the independence between the near-end signal and the reference signals, and is less sensitive to the mismatch of nonlinearity between the numerical and actual models.

Nonlinear Residual Echo Suppression using a Recurrent Neural Network

rrbluke/NRES Interspeech 2020

The acoustic front-end of hands-free communication de-vices introduces a variety of distortions to the linear echo pathbetween the loudspeaker and the microphone.

Acoustic echo cancellation with the dual-signal transformation LSTM network

breizhn/DTLN-aec 27 Oct 2020

This paper applies the dual-signal transformation LSTM network (DTLN) to the task of real-time acoustic echo cancellation (AEC).

AEC in a NetShell: On Target and Topology Choices for FCRN Acoustic Echo Cancellation

yangyucheng000/code3 16 Mar 2021

Acoustic echo cancellation (AEC) algorithms have a long-term steady role in signal processing, with approaches improving the performance of applications such as automotive hands-free systems, smart home and loudspeaker devices, or web conference systems.

Acoustic Echo Cancellation with Cross-Domain Learning

rrbluke/CDEC Interspeech 2021

This paper proposes the Cross-Domain Echo-Controller(CDEC), submitted to the Interspeech 2021 AEC-Challenge. The algorithm consists of three building blocks: (i) a Time-Delay Compensation (TDC) module, (ii) a frequency-domainblock-based Acoustic Echo Canceler (AEC), and (iii) a Time-Domain Neural-Network (TD-NN) used as a post-processor. Our system achieves an overall MOS score of 3. 80, while onlyusing 2. 1 million parameters at a system latency of 32ms.

ICASSP 2022 Acoustic Echo Cancellation Challenge

microsoft/AEC-Challenge 27 Feb 2022

This is the third AEC challenge and it is enhanced by including mobile scenarios, adding speech recognition rate in the challenge goal metrics, and making the default sample rate 48 kHz.

Joint Acoustic Echo Cancellation and Blind Source Extraction based on Independent Vector Extraction

thomashaubner/joint_aec_bse 13 May 2022

We describe a joint acoustic echo cancellation (AEC) and blind source extraction (BSE) approach for multi-microphone acoustic frontends.

Semi-blind source separation using convolutive transfer function for nonlinear acoustic echo cancellation

chengguoliang0/audio-samples2 4 Jul 2022

The recently proposed semi-blind source separation (SBSS) method for nonlinear acoustic echo cancellation (NAEC) outperforms adaptive NAEC in attenuating the nonlinear acoustic echo.