{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,26]],"date-time":"2025-10-26T15:03:12Z","timestamp":1761490992088,"version":"3.37.3"},"reference-count":28,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"Korea Environment Industry &amp; Technology Institute"},{"name":"Public Technology Program based on Environmental Policy"},{"name":"Korea Ministry of Environment","award":["2017000210001"],"award-info":[{"award-number":["2017000210001"]}]},{"DOI":"10.13039\/100006754","name":"Army Research Laboratory","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100006754","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Signal Process. Lett."],"published-print":{"date-parts":[[2020]]},"DOI":"10.1109\/lsp.2020.2988199","type":"journal-article","created":{"date-parts":[[2020,4,20]],"date-time":"2020-04-20T19:38:46Z","timestamp":1587411526000},"page":"640-644","source":"Crossref","is-referenced-by-count":4,"title":["Amphibian Sounds Generating Network Based on Adversarial Learning"],"prefix":"10.1109","volume":"27","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6817-4846","authenticated-orcid":false,"given":"Sangwook","family":"Park","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2597-738X","authenticated-orcid":false,"given":"Mounya","family":"Elhilali","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5055-5408","authenticated-orcid":false,"given":"David K.","family":"Han","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8744-4514","authenticated-orcid":false,"given":"Hanseok","family":"Ko","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref10","first-page":"2672","article-title":"Generative adversarial networks","author":"goodfellow","year":"2014","journal-title":"Proc Advances Neural Inf Process Syst"},{"key":"ref11","first-page":"2107","article-title":"Learning from simulated and unsupervised images through adversarial training","author":"shrivastava","year":"2016","journal-title":"Proc Int Conf Comput Vision Pattern Recognit"},{"key":"ref12","article-title":"The effectiveness of data augmentation in image classification using deep learning","author":"wang","year":"2017","journal-title":"arXiv 1712 04621"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-14815-7_24"},{"article-title":"BAGAN: Data augmentation with balancing GAN","year":"2018","author":"mariani","key":"ref14"},{"key":"ref15","first-page":"5769","article-title":"Improved training of Wasserstein GANs","author":"gulrajani","year":"2017","journal-title":"Proc Advances Neural Inf Process Syst"},{"key":"ref16","first-page":"1","article-title":"On the regularization of Wasserstein GANs","author":"augustin","year":"2018","journal-title":"Proc Int Conf Learn Representations"},{"key":"ref17","first-page":"2018","article-title":"Stabilizing training of generative adversarial networks through regularization","author":"roth","year":"2017","journal-title":"Proc Advances Neural Inf Process Syst"},{"key":"ref18","first-page":"2172","article-title":"InfoGAN: Interpretable representation learning by information maximizing generative adversarial nets","author":"chen","year":"0","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref19","first-page":"93","article-title":"Generative adversarial network based acoustic scene training set augmentation and selection using SVM hyper plane","author":"mun","year":"2017","journal-title":"Workshop on Detection and Classification of Acoustic Scenes and Events (DCASE)"},{"key":"ref28","article-title":"BEGAN: Boundary equilibrium generative adversarial networks","author":"berthelot","year":"2017","journal-title":"arXiv 1703 10717"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2017.7952639"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1155\/2014\/146040"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1145\/2948992.2949016"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.ecoinf.2009.06.005"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/EMBC.2018.8512408"},{"article-title":"Auto-encoding variational bayes","year":"2013","author":"kingma","key":"ref8"},{"key":"ref7","first-page":"37","article-title":"Autoencoders, unsupervised learning, and deep architectures","author":"baldi","year":"2012","journal-title":"Proc ICML Workshop Unsupervised Transfer Learn"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1670\/0022-1511(2006)40[442:CPFASW]2.0.CO;2"},{"article-title":"Tutorial on variational autoencoders","year":"2016","author":"doersch","key":"ref9"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/j.biocon.2003.10.022"},{"article-title":"WaveNet: A generative model for raw audio","year":"2016","author":"van den oord","key":"ref20"},{"article-title":"Least squares generative adversarial networks","year":"2016","author":"mao","key":"ref22"},{"key":"ref21","article-title":"Adversarial audio synthesis","author":"donahue","year":"2018","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/18.61115"},{"article-title":"Wasserstein GAN","year":"2017","author":"arjovsky","key":"ref23"},{"article-title":"Batch normalization: Accelerating deep network training by reducing internal covariate shift","year":"2015","author":"ioffe","key":"ref26"},{"key":"ref25","first-page":"807","article-title":"Rectified linear units improve restricted Boltzmann machines","author":"nair","year":"2010","journal-title":"Proc Int Conf Mach Learn"}],"container-title":["IEEE Signal Processing Letters"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/97\/8966529\/09072273.pdf?arnumber=9072273","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,4,27]],"date-time":"2022-04-27T14:46:32Z","timestamp":1651070792000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9072273\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"references-count":28,"URL":"https:\/\/doi.org\/10.1109\/lsp.2020.2988199","relation":{},"ISSN":["1070-9908","1558-2361"],"issn-type":[{"type":"print","value":"1070-9908"},{"type":"electronic","value":"1558-2361"}],"subject":[],"published":{"date-parts":[[2020]]}}}