On adaptive multichannel dereverberation based on dichotomous coordinate descent and data-reuse techniques
Multichannel linear prediction (MCLP) is widely used for speech dereverberation, with recursive least-squares (RLS)-like algorithms commonly applied to update the linear prediction coefficients. However, these algorithms tend to be computationally intensive, making it necessary in practical implemen...
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| Veröffentlicht in: | Signal processing Jg. 238; S. 110138 |
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| Abstract | Multichannel linear prediction (MCLP) is widely used for speech dereverberation, with recursive least-squares (RLS)-like algorithms commonly applied to update the linear prediction coefficients. However, these algorithms tend to be computationally intensive, making it necessary in practical implementations to reduce complexity while improving numerical robustness for better dereverberation performance. In this paper, we introduce a more efficient MCLP-based adaptive dereverberation method that combines dichotomous coordinate descent (DCD) with a data-reuse (DR) technique. Compared to the traditional RLS-based approach, the proposed method offers two major benefits. First, it significantly lowers computational demands by replacing most multiplications with bitshifts during DCD iterations, making it more suitable for real-world applications. Second, by avoiding the propagation of the inverse covariance matrix via the Riccati equation, the method ensures numerical stability, making it more suitable for processing long-duration speech signals. Additionally, the DR technique improves dereverberation performance by more efficiently utilizing available observed data. Simulation results show that the proposed methods outperform the conventional RLS-based approach in terms of both numerical stability and computational efficiency, while delivering comparable dereverberation performance.
•Novel adaptive dereverberation method incorporating DCD and data reuse.•Efficient multichannel adaptive dereverberation matching RLS performance.•More stable multichannel adaptive dereverberation versus RLS. |
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| AbstractList | Multichannel linear prediction (MCLP) is widely used for speech dereverberation, with recursive least-squares (RLS)-like algorithms commonly applied to update the linear prediction coefficients. However, these algorithms tend to be computationally intensive, making it necessary in practical implementations to reduce complexity while improving numerical robustness for better dereverberation performance. In this paper, we introduce a more efficient MCLP-based adaptive dereverberation method that combines dichotomous coordinate descent (DCD) with a data-reuse (DR) technique. Compared to the traditional RLS-based approach, the proposed method offers two major benefits. First, it significantly lowers computational demands by replacing most multiplications with bitshifts during DCD iterations, making it more suitable for real-world applications. Second, by avoiding the propagation of the inverse covariance matrix via the Riccati equation, the method ensures numerical stability, making it more suitable for processing long-duration speech signals. Additionally, the DR technique improves dereverberation performance by more efficiently utilizing available observed data. Simulation results show that the proposed methods outperform the conventional RLS-based approach in terms of both numerical stability and computational efficiency, while delivering comparable dereverberation performance.
•Novel adaptive dereverberation method incorporating DCD and data reuse.•Efficient multichannel adaptive dereverberation matching RLS performance.•More stable multichannel adaptive dereverberation versus RLS. |
| ArticleNumber | 110138 |
| Author | Yin, Kaili Yang, Wenxing Chen, Jingdong Benesty, Jacob Jin, Jilu |
| Author_xml | – sequence: 1 givenname: Wenxing orcidid: 0000-0003-0395-7003 surname: Yang fullname: Yang, Wenxing email: wenxingyang@usst.edu.cn organization: School of Oriental Pan-Vascular Devices Innovation College, University of Shanghai for Science and Technology, 516 Jungong Road, Shanghai, 200093, China – sequence: 2 givenname: Jilu orcidid: 0000-0003-2967-8379 surname: Jin fullname: Jin, Jilu email: jilu.jin@mail.nwpu.edu.cn organization: Center of Intelligent Acoustics and Immersive Communications, Northwestern Polytechnical University, 127 Youyi West Road, Xi’an, 710072, Shaanxi, China – sequence: 3 givenname: Kaili orcidid: 0000-0002-9754-9651 surname: Yin fullname: Yin, Kaili email: kl_yin@hotmail.com organization: College of Automation and Electronic Engineering, Qingdao University of Science and Technology, 516 JungongRoad, Qingdao, 266520, Shandong, China – sequence: 4 givenname: Jingdong orcidid: 0000-0003-0083-9247 surname: Chen fullname: Chen, Jingdong email: jingdongchen@ieee.org organization: Center of Intelligent Acoustics and Immersive Communications, Northwestern Polytechnical University, 127 Youyi West Road, Xi’an, 710072, Shaanxi, China – sequence: 5 givenname: Jacob orcidid: 0000-0002-0036-5865 surname: Benesty fullname: Benesty, Jacob email: jacob.benesty@inrs.ca organization: INRS-EMT, University of Quebec, 800 de la Gauchetiere Ouest, Montreal, QC H5A 1K6, Canada |
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| Cites_doi | 10.1109/ICASSP.2019.8683294 10.1109/TASLP.2020.3045561 10.1109/MSP.2012.2205029 10.1109/ICASSP48485.2024.10446330 10.1109/LSP.2021.3099715 10.1109/ICASSP39728.2021.9414736 10.1109/TASL.2007.911054 10.3390/app13042227 10.1109/78.91147 10.1109/TASL.2006.889720 10.1109/29.1509 10.1109/TSP.2008.917874 10.1121/1.1570439 10.1109/IWAENC.2014.6954309 10.1109/LSP.2022.3153207 10.1109/LSP.2016.2616888 10.1109/TSP.2020.2997201 10.1109/TASLP.2015.2469142 10.1109/LSP.2020.3044796 10.1109/ICC.2007.422 10.1109/ICASSP40776.2020.9054393 10.1109/TASL.2008.2008042 10.1121/1.5094338 10.21437/Interspeech.2017-733 10.1109/TASLP.2016.2518804 10.1109/ICASSP.2019.8682834 10.1109/TASLP.2018.2811184 10.1109/TASL.2010.2052251 10.1109/TASLP.2015.2418571 10.1109/LSP.2016.2640939 10.1109/TASL.2008.2004306 10.1109/ICASSP.2009.4960438 10.1109/TASLP.2020.2966869 10.1121/1.5051640 10.1121/1.382599 10.1109/TSP.2013.2258340 10.1109/LSP.2019.2911179 10.1109/IWAENC.2018.8521286 10.1109/ICASSP.2008.4517552 10.1109/TASLP.2018.2862826 |
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| Keywords | Adaptive dereverberation Multichannel linear prediction Recursive least-squares algorithm Data-reuse Dichotomous coordinate descent |
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