{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,7]],"date-time":"2026-08-07T15:25:22Z","timestamp":1786116322671,"version":"build-2736575974"},"reference-count":25,"publisher":"Wiley","issue":"15","license":[{"start":{"date-parts":[[2026,7,27]],"date-time":"2026-07-27T00:00:00Z","timestamp":1785110400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,7,27]],"date-time":"2026-07-27T00:00:00Z","timestamp":1785110400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Concurrency and Computation"],"published-print":{"date-parts":[[2026,8]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>In speech signal processing, noise interference during transmission or recording remains a persistent challenge. To address this, we propose a hybrid denoising method combining Grey Wolf Optimizer\u2010Variational Mode Decomposition (GWO\u2010VMD) with Tunable\u2010Q Wavelet Transform (TQWT). First, the GWO algorithm is utilized to optimize the VMD decomposition parameter combination, specifically the number of modes and the penalty factor. Based on the correlation coefficient screening principle, the Intrinsic Mode Function (IMF) components with relatively low correlation coefficients are then removed. Next, the remaining IMFs are recombined, and multi\u2010scale analysis is conducted through TQWT. Finally, the sub\u2010band components whose relative energy exceeds a certain threshold are reconstructed to obtain the denoised signal. For the original three\u2010segment noisy speech signals, the signal\u2010to\u2010noise ratio (SNR) has been remarkably enhanced by using the GWO\u2010VMD\u2010TQWT denoising method. It has increased from \u22121.2227, 8.4398, \u22124.6318 to 11.4980, 19.2606, 6.1067\u2009dB, respectively. Additionally, the root mean square error of this algorithm after denoising is the smallest among the compared methods. Evidently, the joint denoising method in this study outperforms single VMD, TQWT, and classical denoising techniques like EMD, EWT, and CEEMDAN. It provides an effective solution for low SNR speech signal denoising.<\/jats:p>","DOI":"10.1002\/cpe.70802","type":"journal-article","created":{"date-parts":[[2026,7,28]],"date-time":"2026-07-28T05:53:28Z","timestamp":1785218008000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Speech Signal Denoising Based on\n                    <scp>GWO<\/scp>\n                    \u2010\n                    <scp>VMD<\/scp>\n                    Combined With\n                    <scp>TQWT<\/scp>"],"prefix":"10.1002","volume":"38","author":[{"given":"Haiping","family":"Ren","sequence":"first","affiliation":[{"name":"College of Integrated Circuit Science and Engineering, Tianjin University of Technology  Tianjin China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-9899-6558","authenticated-orcid":false,"given":"Chenggao","family":"Li","sequence":"additional","affiliation":[{"name":"College of Integrated Circuit Science and Engineering, Tianjin University of Technology  Tianjin China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kun","family":"Li","sequence":"additional","affiliation":[{"name":"College of Integrated Circuit Science and Engineering, Tianjin University of Technology  Tianjin China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4525-7558","authenticated-orcid":false,"given":"Juan","family":"Qin","sequence":"additional","affiliation":[{"name":"College of Integrated Circuit Science and Engineering, Tianjin University of Technology  Tianjin China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Meng","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Integrated Circuit Science and Engineering, Tianjin University of Technology  Tianjin China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dan","family":"Xia","sequence":"additional","affiliation":[{"name":"College of Integrated Circuit Science and Engineering, Tianjin University of Technology  Tianjin China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shuo","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Integrated Circuit Science and Engineering, Tianjin University of Technology  Tianjin China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiahao","family":"Qi","sequence":"additional","affiliation":[{"name":"College of Integrated Circuit Science and Engineering, Tianjin University of Technology  Tianjin China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,7,27]]},"reference":[{"key":"e_1_2_7_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.apacoust.2020.107817"},{"key":"e_1_2_7_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/B978-0-7506-1162-6.50016-2"},{"key":"e_1_2_7_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cageo.2024.105519"},{"key":"e_1_2_7_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/TASL.2012.2213248"},{"key":"e_1_2_7_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cageo.2023.105464"},{"key":"e_1_2_7_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.optcom.2024.130344"},{"key":"e_1_2_7_8_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jappgeo.2022.104751"},{"key":"e_1_2_7_9_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.measurement.2023.113306"},{"key":"e_1_2_7_10_1","first-page":"US5983162A","article-title":"Computer Implicated Empirical Mode Decomposi\u2010Tion Method Apparatus and Article of Manufacture","volume":"5","author":"Huang N. E.","year":"1996","journal-title":"USA Pro\u2010Visional Application"},{"key":"e_1_2_7_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jocs.2023.102181"},{"key":"e_1_2_7_12_1","doi-asserted-by":"publisher","DOI":"10.3390\/s19143125"},{"key":"e_1_2_7_13_1","doi-asserted-by":"publisher","DOI":"10.18280\/ts.380217"},{"key":"e_1_2_7_14_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2020.102337"},{"key":"e_1_2_7_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2013.2288675"},{"key":"e_1_2_7_16_1","doi-asserted-by":"publisher","DOI":"10.3390\/mi9050246"},{"key":"e_1_2_7_17_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ymssp.2023.110358"},{"key":"e_1_2_7_18_1","doi-asserted-by":"publisher","DOI":"10.1155\/2021\/6640387"},{"key":"e_1_2_7_19_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.infrared.2024.105204"},{"key":"e_1_2_7_20_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2011.2143711"},{"key":"e_1_2_7_21_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2021.3049118"},{"key":"e_1_2_7_22_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.measurement.2022.111914"},{"key":"e_1_2_7_23_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jqsrt.2023.108807"},{"key":"e_1_2_7_24_1","doi-asserted-by":"publisher","DOI":"10.3390\/e24010037"},{"key":"e_1_2_7_25_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.measurement.2023.113854"},{"key":"e_1_2_7_26_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.specom.2023.102972"}],"container-title":["Concurrency and Computation: Practice and Experience"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/cpe.70802","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/full-xml\/10.1002\/cpe.70802","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/cpe.70802","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,8,6]],"date-time":"2026-08-06T08:47:48Z","timestamp":1786006068000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/cpe.70802"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7,27]]},"references-count":25,"journal-issue":{"issue":"15","published-print":{"date-parts":[[2026,8]]}},"alternative-id":["10.1002\/cpe.70802"],"URL":"https:\/\/doi.org\/10.1002\/cpe.70802","archive":["Portico"],"relation":{},"ISSN":["1532-0626","1532-0634"],"issn-type":[{"value":"1532-0626","type":"print"},{"value":"1532-0634","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,7,27]]},"assertion":[{"value":"2025-03-24","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-06-05","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-07-27","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"e70802"}}