{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,28]],"date-time":"2026-07-28T23:15:40Z","timestamp":1785280540663,"version":"3.55.0"},"reference-count":97,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"7","license":[{"start":{"date-parts":[[2025,10,1]],"date-time":"2025-10-01T00:00:00Z","timestamp":1759276800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,10,1]],"date-time":"2025-10-01T00:00:00Z","timestamp":1759276800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,10,1]],"date-time":"2025-10-01T00:00:00Z","timestamp":1759276800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100002341","name":"Research Council of Finland","doi-asserted-by":"publisher","award":["349605"],"award-info":[{"award-number":["349605"]}],"id":[{"id":"10.13039\/501100002341","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE J. Sel. Top. Signal Process."],"published-print":{"date-parts":[[2025,10]]},"DOI":"10.1109\/jstsp.2025.3569430","type":"journal-article","created":{"date-parts":[[2025,5,16]],"date-time":"2025-05-16T13:44:24Z","timestamp":1747403064000},"page":"1542-1557","source":"Crossref","is-referenced-by-count":3,"title":["Shortcut Learning in Binary Classifier Black Boxes: Applications to Voice Anti-Spoofing and Biometrics"],"prefix":"10.1109","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0624-2903","authenticated-orcid":false,"given":"Md","family":"Sahidullah","sequence":"first","affiliation":[{"name":"TCG CREST, Kolkata, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hye-jin","family":"Shim","sequence":"additional","affiliation":[{"name":"Carnegie Mellon University, Pittsburgh, PA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4140-5309","authenticated-orcid":false,"given":"Rosa Gonzalez","family":"Hautam\u00e4ki","sequence":"additional","affiliation":[{"name":"University of Oulu, Oulu, Finland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4371-7322","authenticated-orcid":false,"given":"Tomi H.","family":"Kinnunen","sequence":"additional","affiliation":[{"name":"School of Computing, University of Eastern Finland (UEF), Joensuu, Finland"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/0167-6393(90)90010-7"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/S0167-6393(99)00080-1"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.csl.2019.101027"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/j.csl.2020.101114"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2011.5995347"},{"key":"ref6","article-title":"A decades battle on dataset bias: Are we there yet?","author":"Liu","year":"2024"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1038\/s42256-020-00257-z"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01231-1_31"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1016\/j.dsp.2017.10.011"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00922"},{"key":"ref11","article-title":"Noise or signal: The role of image backgrounds in object recognition","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Xiao","year":"2021"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01626"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2021.07.015"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-28954-6"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1890\/07-2153.1"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/AVSS.2015.7301739"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00607"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1126\/scirobotics.aay7120"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2870052"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2019.12.012"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/WACV48630.2021.00159"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01456"},{"key":"ref23","article-title":"Dont take the easy way out: Ensemble based methods for avoiding known dataset biases","volume-title":"Proc. EMNLP-IJCNLP","author":"Clark","year":"2019"},{"key":"ref24","first-page":"528","article-title":"Learning de-biased representations with biased representations","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Bahng","year":"2020"},{"key":"ref25","first-page":"20673","article-title":"Learning from failure: De-biasing classifier from biased classifier","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Nam","year":"2020"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1016\/j.specom.2022.04.005"},{"key":"ref27","article-title":"ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Geirhos","year":"2019"},{"key":"ref28","first-page":"841","article-title":"RUBi: Reducing unimodal biases for visual question answering","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Cadene","year":"2019"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.11613\/BM.2014.022"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.18637\/jss.v067.i01"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.21437\/ASVSPOOF.2021-9"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/SLT.2018.8639666"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/SLT54892.2023.10022624"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.21437\/Interspeech.2019-2607"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/TASLP.2023.3285283"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.21437\/Interspeech.2023-1901"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.5962\/bhl.title.56164"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511803161"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1207\/S15328031US0202_03"},{"key":"ref40","article-title":"Spurious correlations in machine learning: A survey","author":"Ye","year":"2024"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1145\/3457607"},{"key":"ref42","volume-title":"Pattern Recognition and Machine Learning","author":"Bishop","year":"2006"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1007\/978-0-387-84858-7"},{"key":"ref44","first-page":"9573","article-title":"The pitfalls of simplicity bias in neural networks","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Shah","year":"2020"},{"key":"ref45","article-title":"Fairness and machine learning: Limitations and opportunities","author":"Barocas","year":"2019"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.21437\/Interspeech.2024-1158"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2011.06.019"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9781139024716"},{"key":"ref49","article-title":"SmoothGrad: Removing noise by adding noise","author":"Smilkov","year":"2017"},{"key":"ref50","first-page":"1","article-title":"Voice recognition still has significant race and gender biases","volume":"10","author":"Bajorek","year":"2019","journal-title":"Harvard Bus. Rev."},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1915768117"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2014.2330697"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.21437\/interspeech.2024-1018"},{"key":"ref54","article-title":"The unreliability of acoustic systems in Alzheimers speech datasets with heterogeneous recording conditions","author":"Gauder","year":"2024"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/TASLP.2022.3172632"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2018.8461467"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.21437\/interspeech.2021-1281"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.21437\/Interspeech.2021-1180"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP49357.2023.10095150"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP49357.2023.10095572"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1109\/BIOSIG58226.2023.10345975"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1145\/3531146.3533089"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.21437\/interspeech.2022-10799"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1016\/j.csl.2022.101481"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1109\/IJCB57857.2023.10449225"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1109\/TBIOM.2024.3446846"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP48485.2024.10445935"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP48485.2024.10447137"},{"key":"ref69","doi-asserted-by":"publisher","DOI":"10.21437\/ICSLP.1998-244"},{"key":"ref70","article-title":"Quantifying spuriousness of biased datasets using partial information decomposition","volume-title":"Proc. ICML Workshop Data-Centric Mach. Learning: Datasets Found. Models","author":"Halder","year":"2024"},{"key":"ref71","article-title":"Spurious correlations and where to find them","volume-title":"Proc. ICML Workshop Spurious Correlations, Invariance, Stability","author":"Sreekumar","year":"2023"},{"key":"ref72","doi-asserted-by":"publisher","DOI":"10.1214\/21-SS133"},{"key":"ref73","first-page":"16942","article-title":"Causal discovery from observational and interventional data across multiple environments","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Li","year":"2023"},{"key":"ref74","first-page":"26548","article-title":"Partial counterfactual identification from observational and experimental data","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Zhang","year":"2022"},{"key":"ref75","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-020-17478-w"},{"key":"ref76","doi-asserted-by":"publisher","DOI":"10.1201\/9781439800225"},{"key":"ref77","doi-asserted-by":"publisher","DOI":"10.1016\/j.csl.2005.08.001"},{"key":"ref78","doi-asserted-by":"publisher","DOI":"10.1111\/j.1751-5823.2012.00183.x"},{"key":"ref79","volume-title":"Probabilistic machine learning: Advanced topics","author":"Murphy","year":"2023"},{"issue":"156","key":"ref80","first-page":"1","article-title":"Integrating random effects in deep neural networks","volume":"24","author":"Simchoni","year":"2023","journal-title":"J. Mach. Learn. Res."},{"key":"ref81","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00793"},{"key":"ref82","doi-asserted-by":"publisher","DOI":"10.1080\/10618600.2019.1637747"},{"key":"ref83","doi-asserted-by":"publisher","DOI":"10.1016\/j.artint.2018.07.007"},{"key":"ref84","doi-asserted-by":"publisher","DOI":"10.1002\/0470870109"},{"key":"ref85","doi-asserted-by":"publisher","DOI":"10.2307\/2984875"},{"key":"ref86","doi-asserted-by":"publisher","DOI":"10.21437\/Interspeech.2015-472"},{"key":"ref87","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP43922.2022.9747766"},{"key":"ref88","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP43922.2022.9746213"},{"key":"ref89","doi-asserted-by":"publisher","DOI":"10.1016\/j.csl.2019.101032"},{"key":"ref90","first-page":"263","article-title":"The effect of target\/non-target age difference on speaker recognition performance","volume-title":"Proc. Odyssey","author":"Doddington","year":"2012"},{"key":"ref91","doi-asserted-by":"publisher","DOI":"10.21437\/Interspeech.2021-941"},{"key":"ref92","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2024.emnlp-main.471"},{"key":"ref93","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01010"},{"key":"ref94","first-page":"18600","article-title":"Can I trust my fairness metric? Assessing fairness with unlabeled data and bayesian inference","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Ji","year":"2020"},{"key":"ref95","doi-asserted-by":"publisher","DOI":"10.21437\/ASVspoof.2024-1"},{"key":"ref96","doi-asserted-by":"publisher","DOI":"10.21437\/Interspeech.2013-406"},{"key":"ref97","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2004.1327255"}],"container-title":["IEEE Journal of Selected Topics in Signal Processing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/4200690\/11320985\/11005965.pdf?arnumber=11005965","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,12]],"date-time":"2026-02-12T20:59:45Z","timestamp":1770929985000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11005965\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10]]},"references-count":97,"journal-issue":{"issue":"7"},"URL":"https:\/\/doi.org\/10.1109\/jstsp.2025.3569430","relation":{},"ISSN":["1932-4553","1941-0484"],"issn-type":[{"value":"1932-4553","type":"print"},{"value":"1941-0484","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,10]]}}}