{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,25]],"date-time":"2025-10-25T19:07:42Z","timestamp":1761419262616,"version":"3.41.0"},"reference-count":24,"publisher":"Association for Computing Machinery (ACM)","issue":"4","license":[{"start":{"date-parts":[[2018,10,23]],"date-time":"2018-10-23T00:00:00Z","timestamp":1540252800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"Fujian Educational Committee","award":["JAT160036"],"award-info":[{"award-number":["JAT160036"]}]},{"DOI":"10.13039\/501100011002","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61772571"],"award-info":[{"award-number":["61772571"]}],"id":[{"id":"10.13039\/501100011002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Multimedia Comput. Commun. Appl."],"published-print":{"date-parts":[[2018,11,30]]},"abstract":"<jats:p>This article deals with the problem of Electric Network Frequency (ENF) estimation where Signal to Noise Ratio (SNR) is an essential challenge. By exploiting the low-rank structure of the ENF signal from the audio spectrogram, we propose an approach based on robust principle component analysis to get rid of the interference from speech contents and some of the background noise, which in our case can be regarded as sparse in nature. Weighted linear prediction is enforced on the low-rank signal subspace to gain accurate ENF estimation. The performance of the proposed scheme is analyzed and evaluated as a function of SNR, and the Cram\u00e9r-Rao Lower Bound (CRLB) is approached at an SNR level above -10 dB. Experiments on real datasets have demonstrated the advantages of the proposed method over state-of-the-art work in terms of estimation accuracy. Specifically, the proposed scheme can effectively capture the ENF fluctuations along the time axis using small numbers of signal observations while preserving sufficient frequency precision.<\/jats:p>","DOI":"10.1145\/3241058","type":"journal-article","created":{"date-parts":[[2018,10,23]],"date-time":"2018-10-23T12:16:16Z","timestamp":1540296976000},"page":"1-13","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":15,"title":["Robust Electric Network Frequency Estimation with Rank Reduction and Linear Prediction"],"prefix":"10.1145","volume":"14","author":[{"given":"Xiaodan","family":"Lin","sequence":"first","affiliation":[{"name":"Sun Yat-Sen University, Huaqiao University, Xiamen, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3134-0353","authenticated-orcid":false,"given":"Xiangui","family":"Kang","sequence":"additional","affiliation":[{"name":"Sun Yat-Sen University, Guangzhou, China"}]}],"member":"320","published-online":{"date-parts":[[2018,10,23]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"crossref","unstructured":"Catalin Grigoras. 2005. Digital audio recording analysis: The electric network frequency (ENF) criterion. International Journal of Speech Language 8 the Law 12 1 63--76.  Catalin Grigoras. 2005. Digital audio recording analysis: The electric network frequency (ENF) criterion. International Journal of Speech Language 8 the Law 12 1 63--76.","DOI":"10.1558\/sll.2005.12.1.63"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.forsciint.2006.06.033"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2008.931080"},{"key":"e_1_2_1_4_1","volume-title":"Proceedings of the 33rd International Conference on Audio Forensics-Theory and Practice.","author":"Sanders Richard W.","year":"2008","unstructured":"Richard W. Sanders . 2008 . Digital audio authenticity using the electric network frequency . In Proceedings of the 33rd International Conference on Audio Forensics-Theory and Practice. Richard W. Sanders. 2008. Digital audio authenticity using the electric network frequency. In Proceedings of the 33rd International Conference on Audio Forensics-Theory and Practice."},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2010.2051270"},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2014.2363524"},{"key":"e_1_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2016.2636095"},{"key":"e_1_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2013.2272217"},{"key":"e_1_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/WIFS.2012.6412627"},{"key":"e_1_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-03521-0_11"},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2015.2398367"},{"volume-title":"Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing. IEEE","author":"Su Hui","key":"e_1_2_1_12_1","unstructured":"Hui Su , Adi Hajj-Ahmad , Min Wu , and Douglas W. Oard . 2014. Exploring the use of ENF for multimedia synchronization . In Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing. IEEE , Florence, Italy, 4613--4617. Hui Su, Adi Hajj-Ahmad, Min Wu, and Douglas W. Oard. 2014. Exploring the use of ENF for multimedia synchronization. In Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing. IEEE, Florence, Italy, 4613--4617."},{"key":"e_1_2_1_13_1","volume-title":"Ahmet Emir Dirik, and Nasir Memon","author":"Vatansever Saffet","year":"2017","unstructured":"Saffet Vatansever , Ahmet Emir Dirik, and Nasir Memon . 2017 . Detecting the presence of ENF signal in digital videos: a superpixel based approach. IEEE Signal Processing Letters PP( 99), 1--1. Saffet Vatansever, Ahmet Emir Dirik, and Nasir Memon. 2017. Detecting the presence of ENF signal in digital videos: a superpixel based approach. IEEE Signal Processing Letters PP(99), 1--1."},{"key":"e_1_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1109\/LSP.2016.2537201"},{"key":"e_1_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2013.2265088"},{"key":"e_1_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1109\/TAP.1986.1143830"},{"key":"e_1_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/29.32276"},{"key":"e_1_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2012.2197391"},{"key":"e_1_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2013.2253462"},{"key":"e_1_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.1974.1055282"},{"key":"e_1_2_1_21_1","first-page":"3","article-title":"Robust principal component analysis","volume":"58","author":"Candes Emmanuel J.","year":"2009","unstructured":"Emmanuel J. Candes , Xiaodong Li , Yi Ma , and John Wright . 2009 . Robust principal component analysis ? Journal of the ACM 58 , 3 , 11. Emmanuel J. Candes, Xiaodong Li, Yi Ma, and John Wright. 2009. Robust principal component analysis? Journal of the ACM 58, 3, 11.","journal-title":"Journal of the ACM"},{"key":"e_1_2_1_22_1","unstructured":"Zhouchen Lin Minming Chen and Yi Ma. 2009. The augmented lagrange multiplier method for exact recovery of corrupted low-rank matrices. Eprint Arxiv 9.  Zhouchen Lin Minming Chen and Yi Ma. 2009. The augmented lagrange multiplier method for exact recovery of corrupted low-rank matrices. Eprint Arxiv 9."},{"key":"e_1_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1109\/82.661657"},{"key":"e_1_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1109\/LSP.2013.2272523"}],"container-title":["ACM Transactions on Multimedia Computing, Communications, and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3241058","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3241058","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T00:43:46Z","timestamp":1750207426000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3241058"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,10,23]]},"references-count":24,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2018,11,30]]}},"alternative-id":["10.1145\/3241058"],"URL":"https:\/\/doi.org\/10.1145\/3241058","relation":{},"ISSN":["1551-6857","1551-6865"],"issn-type":[{"type":"print","value":"1551-6857"},{"type":"electronic","value":"1551-6865"}],"subject":[],"published":{"date-parts":[[2018,10,23]]},"assertion":[{"value":"2018-01-01","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2018-07-01","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2018-10-23","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}