{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T12:46:16Z","timestamp":1777639576564,"version":"3.51.4"},"reference-count":47,"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":"Tencent AI Lab"},{"name":"RGC of Hong Kong SAR","award":["PolyU 152137\/17E"],"award-info":[{"award-number":["PolyU 152137\/17E"]}]},{"name":"Tencent AI Lab Rhino-Bird Gift Fund"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE\/ACM Trans. Audio Speech Lang. Process."],"published-print":{"date-parts":[[2020]]},"DOI":"10.1109\/taslp.2020.3030499","type":"journal-article","created":{"date-parts":[[2020,10,14]],"date-time":"2020-10-14T19:40:46Z","timestamp":1602704446000},"page":"2810-2822","source":"Crossref","is-referenced-by-count":15,"title":["A Framework for Adapting DNN Speaker Embedding Across Languages"],"prefix":"10.1109","volume":"28","author":[{"given":"Weiwei","family":"Lin","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Man-Wai","family":"Mak","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Na","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dan","family":"Su","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dong","family":"Yu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref39","article-title":"Unsupervised data augmentation","author":"xie","year":"2019","journal-title":"arXiv 1904 12848"},{"key":"ref38","first-page":"97","article-title":"Learning transferable features with deep adaptation networks","author":"long","year":"0","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref33","first-page":"249","article-title":"Analysis of i-vector length normalization in speaker recognition systems","author":"garcia-romero","year":"0","journal-title":"Proc INTERSPEECH"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.243"},{"key":"ref31","doi-asserted-by":"crossref","first-page":"144","DOI":"10.1109\/TPAMI.2011.104","article-title":"Probabilistic models for inference about identity","volume":"34","author":"li","year":"2012","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"ref30","first-page":"3214","article-title":"A time delay neural network architecture for efficient modeling of long temporal contexts","author":"peddinti","year":"0","journal-title":"Proc INTERSPEECH"},{"key":"ref37","first-page":"1718","article-title":"Generative moment matching networks","author":"li","year":"0","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-49409-8_35"},{"key":"ref35","first-page":"513","article-title":"A Kernel method for the two-sample-problem","author":"gretton","year":"0","journal-title":"Proc Adv Neural Inform Process Syst"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.21437\/Odyssey.2018-25"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2019.8682852"},{"key":"ref40","article-title":"Adversarial examples improve image recognition","author":"xie","year":"2019","journal-title":"arXiv 1911 09665"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.21437\/Odyssey.2018-23"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TASLP.2018.2866707"},{"key":"ref13","first-page":"6236","article-title":"Multi-level deep neural network adaptation for speaker verification using MMD and consistency regularization","author":"lin","year":"0","journal-title":"Proc ICASSP"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.21437\/Interspeech.2019-2168"},{"key":"ref15","article-title":"Auto-encoding variational Bayes","author":"kingma","year":"0","journal-title":"Proc Int Conf Learn Representations"},{"key":"ref16","first-page":"2096","article-title":"Domain-adversarial training of neural networks","volume":"17","author":"ganin","year":"2016","journal-title":"J Mach Learn Res"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP40776.2020.9053735"},{"key":"ref18","first-page":"1157","article-title":"Auto-encoding total correlation explanation","volume":"89","author":"gao","year":"0","journal-title":"Mach Learn Res"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1006\/csla.1996.0013"},{"key":"ref28","first-page":"214","article-title":"Wasserstein generative adversarial networks","volume":"70","author":"arjovsky","year":"0","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.21437\/Interspeech.2017-458"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2019.8683616"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-58347-1_1"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2018.8461375"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2019.8682064"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.21437\/Interspeech.2017-1521"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.21437\/Interspeech.2017-1498"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.21437\/Interspeech.2017-203"},{"key":"ref2","article-title":"Domain adaptation: Learning bounds and algorithms","author":"mansour","year":"2009"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-58347-1_8"},{"key":"ref1","first-page":"129","article-title":"Impossibility theorems for domain adaptation","author":"david","year":"0","journal-title":"Proc 13th Int Conf Artif Intell Statist"},{"key":"ref46","first-page":"2200","article-title":"MMD GAN: Towards deeper understanding of moment matching network","author":"li","year":"0","journal-title":"Proc Adv Neural Inform Process Syst"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1006\/csla.1995.0010"},{"key":"ref45","first-page":"585","article-title":"A Kernel statistical test of independence","author":"gretton","year":"2008","journal-title":"Adv Neural Inform Process Syst"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1006\/csla.1998.0043"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1016\/j.specom.2017.05.004"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TASL.2012.2198059"},{"key":"ref42","first-page":"8024","article-title":"PyTorch: An imperative style, high-performance deep learning library","author":"paszke","year":"2019","journal-title":"Adv Neural Inf Process Sys"},{"key":"ref24","author":"yu","year":"2016","journal-title":"Automatic Speech Recognition"},{"key":"ref41","article-title":"Adam: A method for stochastic optimization","author":"kingma","year":"0","journal-title":"Proc Int Conf Learn Representations"},{"key":"ref23","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1016\/S0167-6393(97)00061-7","article-title":"Speech recognition in noisy environments using first-order vector Taylor series","volume":"24","author":"un","year":"1998","journal-title":"Speech Communication"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01261-8_1"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/ASRU.2017.8268911"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2017.7953152"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2016.11.063"}],"container-title":["IEEE\/ACM Transactions on Audio, Speech, and Language Processing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6570655\/8938144\/09224137.pdf?arnumber=9224137","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,4,27]],"date-time":"2022-04-27T17:31:22Z","timestamp":1651080682000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9224137\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"references-count":47,"URL":"https:\/\/doi.org\/10.1109\/taslp.2020.3030499","relation":{},"ISSN":["2329-9290","2329-9304"],"issn-type":[{"value":"2329-9290","type":"print"},{"value":"2329-9304","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020]]}}}