{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T01:12:29Z","timestamp":1760058749088,"version":"build-2065373602"},"reference-count":34,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2025,4,24]],"date-time":"2025-04-24T00:00:00Z","timestamp":1745452800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Natural Science Foundation of Hunan Province","award":["2025JJ50743","24A0196"],"award-info":[{"award-number":["2025JJ50743","24A0196"]}]},{"name":"Science Research Projects of Hunan Provincial Education Department","award":["2025JJ50743","24A0196"],"award-info":[{"award-number":["2025JJ50743","24A0196"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Symmetry"],"abstract":"<jats:p>In the field of voice cryptography, detecting forged speech is crucial for secure communication and identity authentication. While most existing spoof detection methods rely on monaural audio, the characteristics of dual-channel signals remain underexplored. To address this, we propose a symmetrical dual-branch detection framework that integrates Res2Net with coordinate attention (Res2NetCA) and a dual-channel heterogeneous graph fusion module (DHGFM). The proposed architecture encodes left and right vocal tract signals into spectrogram and time-domain graphs, and it models both intra- and inter-channel time\u2013frequency dependencies through graph attention mechanisms and fusion strategies. Experimental results on the ASVspoof2019 and ASVspoof2021 LA datasets demonstrate the superior detection performance of our method. Specifically, it achieved an EER of 1.64% and a Min-tDCF of 0.051 on ASVspoof2019, and an EER of 6.76% with a Min-tDCF of 0.3638 on ASVspoof2021, validating the effectiveness and potential of dual-channel modeling in spoofed speech detection.<\/jats:p>","DOI":"10.3390\/sym17050641","type":"journal-article","created":{"date-parts":[[2025,4,24]],"date-time":"2025-04-24T06:18:02Z","timestamp":1745475482000},"page":"641","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Dual-Channel Spoofed Speech Detection Based on Graph Attention Networks"],"prefix":"10.3390","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9855-8234","authenticated-orcid":false,"given":"Yun","family":"Tan","sequence":"first","affiliation":[{"name":"College of Electronic Information and Physics, Central South University of Forestry and Technology, Changsha 410004, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-1729-5705","authenticated-orcid":false,"given":"Xiaoqian","family":"Weng","sequence":"additional","affiliation":[{"name":"College of Electronic Information and Physics, Central South University of Forestry and Technology, Changsha 410004, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiangzhang","family":"Zhu","sequence":"additional","affiliation":[{"name":"College of Electronic Information and Physics, Central South University of Forestry and Technology, Changsha 410004, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,4,24]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"87","DOI":"10.11591\/csit.v2i2.p87-94","article-title":"Designing a secured audio-based key generator for cryptographic symmetric key algorithms","volume":"2","author":"Raghunath","year":"2021","journal-title":"Comput. 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