Residual Echo Suppression using Spatial Feature for Stereo Acoustic Echo Cancellation

Hsuan Cheng Chou*, Yih Liang Shen*, Meng Hsuan Wu*, Bo Wun Shih, Tai Shih Chi*

*Corresponding author for this work

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

Abstract

There have been some advances in deep learning based stereo-AEC (SAEC) systems in recent years. However, most of the studies focused on solving the non-uniqueness problem and did not explore the impact of spatial cues on SAEC. In this paper, we propose a composite SAEC system that combines conventional adaptive filters and Wiener filters with a NN-based residual echo suppression (RES) module. We adopt generalized cross correlation (GCC) as an additional input to allow the RES module to better analyze the embedded spatial cues. Experimental results show that the addition of GCC stably improves system performance with a little computational overhead. In addition, the proposed system achieves better results with much less computation than compared NN-based SAEC systems in all test conditions.

Original languageEnglish
Title of host publication2023 Asia Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2349-2353
Number of pages5
ISBN (Electronic)9798350300673
DOIs
StatePublished - 2023
Event2023 Asia Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2023 - Taipei, Taiwan
Duration: 31 Oct 20233 Nov 2023

Publication series

Name2023 Asia Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2023

Conference

Conference2023 Asia Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2023
Country/TerritoryTaiwan
CityTaipei
Period31/10/233/11/23

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