{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,9]],"date-time":"2026-05-09T04:03:58Z","timestamp":1778299438028,"version":"3.51.4"},"reference-count":47,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2024,8,30]],"date-time":"2024-08-30T00:00:00Z","timestamp":1724976000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2024,8,30]],"date-time":"2024-08-30T00:00:00Z","timestamp":1724976000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100017520","name":"Fakulta Informacn\u00edch Technologi\u00ed, Vysok\u00e9 Ucen\u00ed Technick\u00e9 v Brne","doi-asserted-by":"publisher","award":["FIT-S-23-8151"],"award-info":[{"award-number":["FIT-S-23-8151"]}],"id":[{"id":"10.13039\/501100017520","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100009532","name":"Ministerstvo Vnitra Cesk\u00e9 Republiky","doi-asserted-by":"publisher","award":["VB02000060"],"award-info":[{"award-number":["VB02000060"]}],"id":[{"id":"10.13039\/100009532","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Image Video Proc."],"abstract":"<jats:title>Abstract<\/jats:title><jats:p>In this paper, we undertake a novel two-pronged investigation into the human recognition of deepfake speech, addressing critical gaps in existing research. First, we pioneer an evaluation of the impact of prior information on deepfake recognition, setting our work apart by simulating real-world attack scenarios where individuals are not informed in advance of deepfake exposure. This approach simulates the unpredictability of real-world deepfake attacks, providing unprecedented insights into human vulnerability under realistic conditions. Second, we introduce a novel metric to evaluate the quality of deepfake audio. This metric facilitates a deeper exploration into how the quality of deepfake speech influences human detection accuracy. By examining both the effect of prior knowledge about deepfakes and the role of deepfake speech quality, our research reveals the importance of these factors, contributes to understanding human vulnerability to deepfakes, and suggests measures to enhance human detection skills.<\/jats:p>","DOI":"10.1186\/s13640-024-00641-4","type":"journal-article","created":{"date-parts":[[2024,8,30]],"date-time":"2024-08-30T19:02:18Z","timestamp":1725044538000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Comprehensive multiparametric analysis of human deepfake speech recognition"],"prefix":"10.1186","volume":"2024","author":[{"given":"Kamil","family":"Malinka","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4717-1910","authenticated-orcid":false,"given":"Anton","family":"Firc","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Milan","family":"\u0160alko","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Daniel","family":"Prudk\u00fd","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Karol\u00edna","family":"Rada\u010dovsk\u00e1","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Petr","family":"Han\u00e1\u010dek","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,8,30]]},"reference":[{"issue":"4","key":"641_CR1","doi-asserted-by":"publisher","first-page":"15090","DOI":"10.1016\/j.heliyon.2023.e15090","volume":"9","author":"A Firc","year":"2023","unstructured":"A. Firc, K. Malinka, P. Han\u00e1\u010dek, Deepfakes as a threat to a speaker and facial recognition: An overview of tools and attack vectors. Heliyon 9(4), 15090 (2023). https:\/\/doi.org\/10.1016\/j.heliyon.2023.e15090","journal-title":"Heliyon"},{"key":"641_CR2","doi-asserted-by":"publisher","unstructured":"A. Firc, K. Malinka, The Dawn of a Text-dependent Society: Deepfakes as a Threat to Speech Verification Systems, pp. 1646\u20131655 (2022). https:\/\/doi.org\/10.1145\/3477314.3507013","DOI":"10.1145\/3477314.3507013"},{"key":"641_CR3","doi-asserted-by":"publisher","DOI":"10.1145\/3605098.3635953","author":"M \u0160alko","year":"2024","unstructured":"M. \u0160alko, A. Firc, K. Malinka, Security Implications of Deepfakes in Face Authentication. (2024). https:\/\/doi.org\/10.1145\/3605098.3635953","journal-title":"Security Implications of Deepfakes in Face Authentication."},{"key":"641_CR4","doi-asserted-by":"publisher","first-page":"25494","DOI":"10.1109\/ACCESS.2022.3154404","volume":"10","author":"MS Rana","year":"2022","unstructured":"M.S. Rana, M.N. Nobi, B. Murali, A.H. Sung, Deepfake detection: A systematic literature review. IEEE Access 10, 25494\u201325513 (2022). https:\/\/doi.org\/10.1109\/ACCESS.2022.3154404","journal-title":"IEEE Access"},{"key":"641_CR5","doi-asserted-by":"publisher","unstructured":"Y. Mirsky, W. Lee, The creation and detection of deepfakes: A survey. ACM Comput. Surv. 54(1) (2021) https:\/\/doi.org\/10.1145\/3425780","DOI":"10.1145\/3425780"},{"key":"641_CR6","unstructured":"H. Chen, K. Magramo, Finance worker pays out \\$25 million after video call with Deepfake \u201cchief financial officer\u201d. Cable News Network (2024). https:\/\/edition.cnn.com\/2024\/02\/04\/asia\/deepfake-cfo-scam-hong-kong-intl-hnk\/index.html"},{"key":"641_CR7","unstructured":"T. Brewster, Fraudsters cloned company director\u2019s voice in \\$35 million bank heist, police find. Forbes Magazine (2021). https:\/\/www.forbes.com\/sites\/thomasbrewster\/2021\/10\/14\/huge-bank-fraud-uses-deep-fake-voice-tech-to-steal-millions\/"},{"key":"641_CR8","unstructured":"M. Bajtler, Fale\u0161n\u00e9 videohovory Jsou Tu. Kolegovi Zavolal M\u00e5j Deepfake, \u0159\u00edk\u00e1 Zakladatel Gymbeamu. Forbes (2023). https:\/\/forbes.cz\/falesne-videohovory-jsou-tu-kolegovi-zavolal-muj-deepfake-rika-zakladatel-gymbeamu\/"},{"key":"641_CR9","unstructured":"L. O\u2019Donnell, CEO \u2019Deep fake\u2019 swindles company out of \\$243K (2019). https:\/\/threatpost.com\/deep-fake-of-ceos-voice-swindles-company-out-of-243k\/147982\/"},{"key":"641_CR10","unstructured":"P. Oltermann, European politicians duped into deepfake video calls with mayor of Kyiv. Guardian News and Media (2022). https:\/\/www.theguardian.com\/world\/2022\/jun\/25\/european-leaders-deepfake-video-calls-mayor-of-kyiv-vitali-klitschko"},{"key":"641_CR11","unstructured":"J. Wakefield, Deepfake presidents used in Russia-ukraine war. BBC (2022). https:\/\/www.bbc.com\/news\/technology-60780142"},{"key":"641_CR12","unstructured":"S.M. Kelly, Explicit, ai-generated Taylor Swift images spread quickly on social media. CNN (2024). https:\/\/www.cnn.com\/2024\/01\/25\/tech\/taylor-swift-ai-generated-images\/index.html"},{"key":"641_CR13","doi-asserted-by":"publisher","unstructured":"N.M. M\u00fcller, K. Pizzi, J. Williams, Human perception of audio deepfakes. In: Proceedings of the 1st International Workshop on Deepfake Detection for Audio Multimedia. DDAM \u201922, pp. 85\u201391. Association for Computing Machinery, New York, NY, USA (2022). https:\/\/doi.org\/10.1145\/3552466.3556531","DOI":"10.1145\/3552466.3556531"},{"issue":"8","key":"641_CR14","doi-asserted-by":"publisher","first-page":"0285333","DOI":"10.1371\/journal.pone.0285333","volume":"18","author":"KT Mai","year":"2023","unstructured":"K.T. Mai, S. Bray, T. Davies, L.D. Griffin, Warning: Humans cannot reliably detect speech deepfakes. PLoS ONE 18(8), 0285333 (2023). https:\/\/doi.org\/10.1371\/journal.pone.0285333","journal-title":"PLoS ONE"},{"key":"641_CR15","doi-asserted-by":"publisher","unstructured":"D. Prudk\u00fd, A. Firc, K. Malinka, Assessing the human ability to recognize synthetic speech in ordinary conversation. In: 2023 International Conference of the Biometrics Special Interest Group (BIOSIG), pp. 1\u20135 (2023). https:\/\/doi.org\/10.1109\/BIOSIG58226.2023.10346006","DOI":"10.1109\/BIOSIG58226.2023.10346006"},{"key":"641_CR16","doi-asserted-by":"publisher","unstructured":"X. Wang, J. Yamagishi, M.Todisco, H.Delgado, A. Nautsch, N. Evans, M. Sahidullah, V. Vestman, T. Kinnunen, K.A. Lee, L. Juvela, P. Alku, Y.-H. Peng, H.-T. Hwang, Y. Tsao, H.-M. Wang, S.L. Maguer, M. Becker, F. Henderson, R. Clark, Y. Zhang, Q. Wang, Y.Jia, K. Onuma, K. Mushika, T.Kaneda, Y.Jiang, L.-J. Liu, Y.-C. Wu, W.-C.Huang, T.Toda, K.Tanaka, H. Kameoka, I. Steiner, D. Matrouf, J.-F. Bonastre, A. Govender, S.Ronanki, J.-X. Zhang, Z.-H. Ling, Asvspoof 2019: A large-scale public database of synthesized, converted and replayed speech. Computer Speech & Language 64, 101114 (2020)https:\/\/doi.org\/10.1016\/j.csl.2020.101114","DOI":"10.1016\/j.csl.2020.101114"},{"key":"641_CR17","unstructured":"G. Watson, Z. Khanjani, V.P. Janeja, Audio Deepfake Perceptions in College Going Populations (2021)"},{"key":"641_CR18","doi-asserted-by":"publisher","unstructured":"M. Groh, Z. Epstein, N. Obradovich, M. Cebrian, I. Rahwan, Human detection of machine-manipulated media. Communications of the ACM 64(10), 40\u201347 (2021). https:\/\/doi.org\/10.1145\/3445972. Accessed 2022-12-26","DOI":"10.1145\/3445972"},{"key":"641_CR19","doi-asserted-by":"publisher","unstructured":"S.R. Godage, F. Lovasdaly, S. Venkatesh, K. Raja, R. Ramachandra, C. Busch, Analyzing human observer ability in morphing attack detection -where do we stand? IEEE Transactions on Technology and Society, 1\u20131 (2023) https:\/\/doi.org\/10.1109\/tts.2022.3231450","DOI":"10.1109\/tts.2022.3231450"},{"key":"641_CR20","doi-asserted-by":"crossref","unstructured":"A, Rossler, D. Cozzolino, L. Verdoliva, C. Riess, J. Thies, M. Nie\u00dfner, FaceForensics++: Learning to Detect Manipulated Facial Images. arXiv. arXiv:1901.08971 [cs] (2019). http:\/\/arxiv.org\/abs\/1901.08971 Accessed 2022-12-26","DOI":"10.1109\/ICCV.2019.00009"},{"key":"641_CR21","unstructured":"P. Korshunov, S. Marcel, Deepfake detection: humans vs. machines. arXiv. arXiv:2009.03155 [cs, eess] (2020). http:\/\/arxiv.org\/abs\/2009.03155 Accessed 2022-12-26"},{"key":"641_CR22","doi-asserted-by":"publisher","unstructured":"M. Groh, Z. Epstein, C. Firestone, R. Picard, Deepfake detection by human crowds, machines, and machine-informed crowds. Proceedings of the National Academy of Sciences 119(1), 2110013119 (2022) https:\/\/doi.org\/10.1073\/pnas.2110013119https:\/\/www.pnas.org\/doi\/pdf\/10.1073\/pnas.2110013119","DOI":"10.1073\/pnas.2110013119"},{"key":"641_CR23","doi-asserted-by":"publisher","unstructured":"R. Tahir, B. Batool, H. Jamshed, M. Jameel, M. Anwar, F. Ahmed, M.A. Zaffar, M.F. Zaffar, Seeing is believing: Exploring perceptual differences in DeepFake videos. In: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems. ACM, ??? (2021). https:\/\/doi.org\/10.1145\/3411764.3445699","DOI":"10.1145\/3411764.3445699"},{"key":"641_CR24","doi-asserted-by":"crossref","unstructured":"M. Groh, A. Sankaranarayanan, N. Singh, D.Y. Kim, A. Lippman, R. Picard, Human Detection of Political Speech Deepfakes across Transcripts, Audio, and Video (2024)","DOI":"10.1038\/s41467-024-51998-z"},{"key":"641_CR25","doi-asserted-by":"publisher","first-page":"470","DOI":"10.1007\/978-3-031-51023-6_39","volume-title":"Image Analysis and Processing - ICIAP 2023 Workshops","author":"SK Jilani","year":"2024","unstructured":"S.K. Jilani, Z. Geradts, A. Abubakar, Decoding deception: Understanding human discrimination ability in differentiating authentic faces from deepfake deceits, in Image Analysis and Processing - ICIAP 2023 Workshops. ed. by G.L. Foresti, A. Fusiello, E. Hancock (Springer, Cham, 2024), pp.470\u2013481"},{"key":"641_CR26","doi-asserted-by":"publisher","unstructured":"S.D. Bray, S.D. Johnson, B. Kleinberg, Testing human ability to detect \u2018deepfake\u2019 images of human faces. Journal of Cybersecurity 9(1) (2023) https:\/\/doi.org\/10.1093\/cybsec\/tyad011","DOI":"10.1093\/cybsec\/tyad011"},{"key":"641_CR27","doi-asserted-by":"publisher","unstructured":"K. Somoray, D.J. Miller, Providing detection strategies to improve human detection of deepfakes: An experimental study. Computers in Human Behavior 149, 107917 (2023) https:\/\/doi.org\/10.1016\/j.chb.2023.107917","DOI":"10.1016\/j.chb.2023.107917"},{"key":"641_CR28","doi-asserted-by":"publisher","unstructured":"M.F.B. Ahmed, M.S.U. Miah, A. Bhowmik, J.B. Sulaiman, Awareness to deepfake: A resistance mechanism to deepfake. In: 2021 International Congress of Advanced Technology and Engineering (ICOTEN), pp. 1\u20135 (2021). https:\/\/doi.org\/10.1109\/ICOTEN52080.2021.9493549","DOI":"10.1109\/ICOTEN52080.2021.9493549"},{"key":"641_CR29","doi-asserted-by":"publisher","unstructured":"V. Matyas, J. Krhovjak, M. Kumpost, D. Cvrcek, Authorizing card payments with pins. Computer 41, 64\u201368 (2008) https:\/\/doi.org\/10.1109\/MC.2008.40","DOI":"10.1109\/MC.2008.40"},{"key":"641_CR30","unstructured":"D. Prudk\u00fd, Assessing the human ability to recognize synthetic speech. Bachelor\u2019s thesis, Brno University of Technology, Brno, Czech republic (2023). https:\/\/www.vut.cz\/en\/students\/final-thesis\/detail\/140541"},{"key":"641_CR31","unstructured":"E. Casanova, J. Weber, C.D. Shulby, A.C. Junior, E. G\u00f6lge, M.A. Ponti, YourTTS: Towards zero-shot multi-speaker TTS and zero-shot voice conversion for everyone. In: Chaudhuri, K., Jegelka, S., Song, L., Szepesvari, C., Niu, G., Sabato, S. (eds.) Proceedings of the 39th International Conference on Machine Learning. Proceedings of Machine Learning Research, vol. 162, pp. 2709\u20132720. PMLR, ??? (2022). https:\/\/proceedings.mlr.press\/v162\/casanova22a.html"},{"key":"641_CR32","doi-asserted-by":"crossref","unstructured":"P.C. Loizou, Speech quality assessment. Multimedia analysis, processing and communications, 623\u2013654 (2011)","DOI":"10.1007\/978-3-642-19551-8_23"},{"key":"641_CR33","unstructured":"K. Martin, New ID R &D research finds over 1 in 3 Americans confident they could detect a computer-generated voice pretending to be a human voice (2020). https:\/\/www.idrnd.ai\/voice-deepfake-survey\/"},{"key":"641_CR34","unstructured":"K. Rada\u010dovsk\u00e1, Deepfake dataset for evaluation of human capability on deepfake recognition. Bachelor\u2019s thesis, Brno University of Technology, Brno, Czech republic (2023). https:\/\/www.vut.cz\/studenti\/zav-prace\/detail\/140539"},{"key":"641_CR35","doi-asserted-by":"publisher","unstructured":"M. Wang, C. Boeddeker, R.G. Dantas, A. Seelan, ludlows\/python-pesq: supporting for multiprocessing features. Zenodo (2022) https:\/\/doi.org\/10.5281\/ZENODO.6549559. https:\/\/zenodo.org\/record\/6549559","DOI":"10.5281\/ZENODO.6549559"},{"key":"641_CR36","unstructured":"M. Shannon, mcd. GitHub (2017)"},{"key":"641_CR37","doi-asserted-by":"publisher","unstructured":"M. MORISE, F. YOKOMORI, K. OZAWA, World: A vocoder-based high-quality speech synthesis system for real-time applications. IEICE Transactions on Information and Systems E99.D(7), 1877\u20131884 (2016) https:\/\/doi.org\/10.1587\/transinf.2015EDP7457","DOI":"10.1587\/transinf.2015EDP7457"},{"key":"641_CR38","unstructured":"R. Ardila, M. Branson, K. Davis, M. Henretty, M. Kohler, J. Meyer, R. Morais, L. Saunders, F.M. Tyers, G. Weber, Common Voice: A Massively-Multilingual Speech Corpus (2020)"},{"issue":"1","key":"641_CR39","first-page":"23","volume":"119","author":"DJ Simons","year":"2010","unstructured":"D.J. Simons, C.F. Chabris, The monkey business illusion. Cognition 119(1), 23\u201332 (2010)","journal-title":"Cognition"},{"key":"641_CR40","unstructured":"A. Firc, Applicability of deepfakes in the field of cyber security. Master\u2019s thesis, Brno University of Technology, Faculty of Information Technology, Brno (2021). Supervisor Mgr. Kamil Malinka, Ph.D"},{"issue":"2","key":"641_CR41","doi-asserted-by":"publisher","first-page":"125","DOI":"10.1109\/TTS.2022.3231450","volume":"4","author":"SR Godage","year":"2023","unstructured":"S.R. Godage, F. L\u00f8v\u00e5sdal, S. Venkatesh, K. Raja, R. Ramachandra, C. Busch, Analyzing human observer ability in morphing attack detection-where do we stand? IEEE Transactions on Technology and Society 4(2), 125\u2013145 (2023). https:\/\/doi.org\/10.1109\/TTS.2022.3231450","journal-title":"IEEE Transactions on Technology and Society"},{"key":"641_CR42","unstructured":"ThoughtCo: These French pronunciation mistakes are toughest for new speakers. ThoughtCo (2019). https:\/\/www.thoughtco.com\/french-pronunciation-mistakes-and-difficulties-1364615"},{"key":"641_CR43","doi-asserted-by":"crossref","unstructured":"D. Liakin, W. Cardoso, N. Liakina, Learning l2 pronunciation with a mobile speech recognizer: French \/y\/. CALICO Journal 32(1), 1\u201325 (2015). Accessed 2024-06-10","DOI":"10.1558\/cj.v32i1.25962"},{"key":"641_CR44","doi-asserted-by":"publisher","unstructured":"M. Westerlund, The emergence of deepfake technology: A review. Technology Innovation Management Review 9, 40\u201353 (2019) https:\/\/doi.org\/10.22215\/timreview\/1282 . Chap. 40","DOI":"10.22215\/timreview\/1282"},{"issue":"2","key":"641_CR45","doi-asserted-by":"publisher","first-page":"252","DOI":"10.3758\/pbr.16.2.252","volume":"16","author":"R Russell","year":"2009","unstructured":"R. Russell, B. Duchaine, K. Nakayama, Super-recognizers: People with extraordinary face recognition ability. Psychonomic Bulletin & Review 16(2), 252\u2013257 (2009). https:\/\/doi.org\/10.3758\/pbr.16.2.252","journal-title":"Psychonomic Bulletin & Review"},{"key":"641_CR46","unstructured":"Malicious Actors Almost Certainly Will Leverage Synthetic Content for Cyber and Foreign Influence Operations. publisher: FBI (2021). https:\/\/www.aha.org\/system\/files\/media\/file\/2021\/03\/fbi-tlp-white-pin-malicious-actors-almost-certainly-will-leverage-synthetic-content-for-cyber-and-foreign-influence-operations-3-10-21.pdf Accessed 2023-04-24"},{"key":"641_CR47","doi-asserted-by":"publisher","unstructured":"A. Firc, K. Malinka, P. Han\u00e1\u010dek, Deepfake speech detection: A spectrogram analysis, pp. 1312\u20131320 (2024). https:\/\/doi.org\/10.1145\/3605098.3635911","DOI":"10.1145\/3605098.3635911"}],"container-title":["EURASIP Journal on Image and Video Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s13640-024-00641-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s13640-024-00641-4\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s13640-024-00641-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,27]],"date-time":"2024-11-27T15:34:09Z","timestamp":1732721649000},"score":1,"resource":{"primary":{"URL":"https:\/\/jivp-eurasipjournals.springeropen.com\/articles\/10.1186\/s13640-024-00641-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,8,30]]},"references-count":47,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2024,12]]}},"alternative-id":["641"],"URL":"https:\/\/doi.org\/10.1186\/s13640-024-00641-4","relation":{},"ISSN":["1687-5281"],"issn-type":[{"value":"1687-5281","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,8,30]]},"assertion":[{"value":"29 February 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 August 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"30 August 2024","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no Conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"24"}}