{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,6]],"date-time":"2026-07-06T20:21:31Z","timestamp":1783369291367,"version":"3.54.6"},"reference-count":39,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["62472135"],"award-info":[{"award-number":["62472135"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Zhejiang Province Key R&D Project","award":["2025C04002"],"award-info":[{"award-number":["2025C04002"]}]},{"name":"Hangzhou Municipal Key R&D Project","award":["2025SZD1A51"],"award-info":[{"award-number":["2025SZD1A51"]}]},{"name":"Sino-French Joint Laboratory for Digital Media Forensics of Zhejiang Province"},{"name":"Zhejiang Provincial Key Laboratory for Sensitive Data Security Protection and Confidentiality Management","award":["2024E10048"],"award-info":[{"award-number":["2024E10048"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Signal Process. Lett."],"published-print":{"date-parts":[[2026]]},"DOI":"10.1109\/lsp.2026.3702794","type":"journal-article","created":{"date-parts":[[2026,6,11]],"date-time":"2026-06-11T20:04:43Z","timestamp":1781208283000},"page":"2580-2584","source":"Crossref","is-referenced-by-count":0,"title":["LAW: A Training-Free Latent Watermark for Diffusion-Generated Audio Attribution"],"prefix":"10.1109","volume":"33","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-2933-0816","authenticated-orcid":false,"given":"Ruizhe","family":"Zhu","sequence":"first","affiliation":[{"name":"School of Cyberspace, Hangzhou Dianzi University, Hangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lingyong","family":"Zou","sequence":"additional","affiliation":[{"name":"School of Cyberspace, Hangzhou Dianzi University, Hangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-5570-1132","authenticated-orcid":false,"given":"Shuhong","family":"Lai","sequence":"additional","affiliation":[{"name":"School of Cyberspace, Hangzhou Dianzi University, Hangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3317-6080","authenticated-orcid":false,"given":"Zhangyi","family":"Shen","sequence":"additional","affiliation":[{"name":"School of Cyberspace, Hangzhou Dianzi University, Hangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-0810-2680","authenticated-orcid":false,"given":"Zhuang","family":"Li","sequence":"additional","affiliation":[{"name":"School of Cyberspace, Hangzhou Dianzi University, Hangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4912-2132","authenticated-orcid":false,"given":"Tong","family":"Qiao","sequence":"additional","affiliation":[{"name":"School of Cyberspace, Hangzhou Dianzi University, Hangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","first-page":"21450","article-title":"AudioLDM: Text-to-audio generation with latent diffusion models","volume-title":"Proc. Int. Conf. Mach. Learn.","volume":"202","author":"Liu","year":"2023"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TASLP.2024.3399607"},{"key":"ref3","article-title":"AudioGen: Textually guided audio generation","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Kreuk","year":"2023"},{"key":"ref4","article-title":"UniAudio: An audio foundation model toward universal audio generation","author":"Yang","year":"2023"},{"key":"ref5","article-title":"WavMark: Watermarking for audio generation","author":"Chen","year":"2023"},{"issue":"8","key":"ref6","article-title":"Fraudsters used AI to mimic CEOs voice in unusual cybercrime case","volume":"30","author":"Stupp","year":"2019","journal-title":"Wall Street J."},{"key":"ref7","article-title":"They thought loved ones were calling for help. It was an AI scam","volume":"10","author":"Verma","year":"2023","journal-title":"Washington Post"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.52202\/075280-2529"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.01156"},{"key":"ref10","first-page":"34688","article-title":"GaussMarker: Robust dual-domain watermark for diffusion models","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Li","year":"2025"},{"key":"ref11","first-page":"118642","article-title":"T2SMark: Balancing robustness and diversity in noise-as-watermark for diffusion models","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"38","author":"Yang","year":"2025"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2026.131831"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-023-14495-x"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.3390\/s22145376"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-10-4289-8"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/18.923725"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1049\/cp.2012.1873"},{"key":"ref18","first-page":"4567","article-title":"A comprehensive real-world assessment of audio watermarking algorithms: Will they survive neural codecs?","volume-title":"Proc. 26th Annu. Conf. Int. Speech Commun. Assoc.","author":"zer","year":"2025"},{"key":"ref19","article-title":"Multi-bit audio watermarking","author":"Lanzendrfer","year":"2025","journal-title":"AI for Music Workshop"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/LSP.2021.3076358"},{"key":"ref21","article-title":"Audio deepfake detection: A survey","author":"Yi","year":"2023"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1145\/3746027.3754568"},{"key":"ref23","article-title":"Adversarial attacks on audio deepfake detection: A benchmark and comparative study","author":"Uddin","year":"2025"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/WACVW65960.2025.00178"},{"key":"ref25","first-page":"1","article-title":"Proactive detection of voice cloning with localized watermarking","volume-title":"Proc. 41st Int. Conf. Mach. Learn.","volume":"235","author":"Roman","year":"2024"},{"key":"ref26","first-page":"38987","article-title":"XAttnMark: Learning robust audio watermarking with cross-attention","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Liu","year":"2025"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.21437\/Interspeech.2024-174"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/LSP.2025.3562817"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1145\/3664647.3680596"},{"key":"ref30","article-title":"SOLIDO: A robust watermarking method for speech synthesis via low-rank adaptation","author":"Li","year":"2025"},{"key":"ref31","article-title":"TriniMark: A robust generative speech watermarking method for trinity-level traceability","author":"Li","year":"2025"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.21437\/Interspeech.2024-534"},{"key":"ref33","article-title":"DiffWave: A versatile diffusion model for audio synthesis","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Kong","year":"2021"},{"key":"ref34","article-title":"WaveGrad: Estimating gradients for waveform generation","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Chen","year":"2021"},{"key":"ref35","article-title":"PriorGrad: Improving conditional denoising diffusion models with data-dependent adaptive prior","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Lee","year":"2022"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/LSP.2025.3600376"},{"key":"ref37","article-title":"The LJ speech dataset","author":"Ito","year":"2017"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2015.7178964"},{"key":"ref39","article-title":"Denoising diffusion implicit models","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Song","year":"2025"}],"container-title":["IEEE Signal Processing Letters"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/97\/11304147\/11558436.pdf?arnumber=11558436","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,6]],"date-time":"2026-07-06T19:58:18Z","timestamp":1783367898000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11558436\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"references-count":39,"URL":"https:\/\/doi.org\/10.1109\/lsp.2026.3702794","relation":{},"ISSN":["1070-9908","1558-2361"],"issn-type":[{"value":"1070-9908","type":"print"},{"value":"1558-2361","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026]]}}}