@inproceedings{c198028493ed45758936d41f2e11aa92,
title = "Residual Echo Suppression using Spatial Feature for Stereo Acoustic Echo Cancellation",
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.",
author = "Chou, {Hsuan Cheng} and Shen, {Yih Liang} and Wu, {Meng Hsuan} and Shih, {Bo Wun} and Chi, {Tai Shih}",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 Asia Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2023 ; Conference date: 31-10-2023 Through 03-11-2023",
year = "2023",
doi = "10.1109/APSIPAASC58517.2023.10317480",
language = "English",
series = "2023 Asia Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2023",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "2349--2353",
booktitle = "2023 Asia Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2023",
address = "美國",
}