{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,30]],"date-time":"2026-04-30T22:54:47Z","timestamp":1777589687738,"version":"3.51.4"},"publisher-location":"New York, NY, USA","reference-count":34,"publisher":"ACM","license":[{"start":{"date-parts":[[2022,10,10]],"date-time":"2022-10-10T00:00:00Z","timestamp":1665360000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"the National Natural Science Foundation of China","award":["No.61831022, No.61901473, No.61771472, No.61773379"],"award-info":[{"award-number":["No.61831022, No.61901473, No.61771472, No.61773379"]}]},{"name":"Inria-CAS Joint Research Project","award":["No.173211KYSB20190049"],"award-info":[{"award-number":["No.173211KYSB20190049"]}]},{"name":"the National Key Research & Development Plan of China","award":["No.2017YFC0820602"],"award-info":[{"award-number":["No.2017YFC0820602"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2022,10,14]]},"DOI":"10.1145\/3552466.3556530","type":"proceedings-article","created":{"date-parts":[[2022,10,1]],"date-time":"2022-10-01T12:27:26Z","timestamp":1664627246000},"page":"27-33","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":27,"title":["Fully Automated End-to-End Fake Audio Detection"],"prefix":"10.1145","author":[{"given":"Chenglong","family":"Wang","sequence":"first","affiliation":[{"name":"University of Science and Technology of China &amp; Institute of Automation, Chinese Academy of Sciences, Hefei, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiangyan","family":"Yi","sequence":"additional","affiliation":[{"name":"Institute of Automation, Chinese Academy of Sciences &amp; University of Chinese Academy of Sciences, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianhua","family":"Tao","sequence":"additional","affiliation":[{"name":"Institute of Automation, Chinese Academy of Sciences &amp; University of Chinese Academy of Sciences, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haiyang","family":"Sun","sequence":"additional","affiliation":[{"name":"Institute of Automation, Chinese Academy of Sciences &amp; University of Chinese Academy of Sciences, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xun","family":"Chen","sequence":"additional","affiliation":[{"name":"University of Science and Technology of China, Hefei, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhengkun","family":"Tian","sequence":"additional","affiliation":[{"name":"Institute of Automation, Chinese Academy of Sciences &amp; University of Chinese Academy of Sciences, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haoxin","family":"Ma","sequence":"additional","affiliation":[{"name":"Institute of Automation, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cunhang","family":"Fan","sequence":"additional","affiliation":[{"name":"Anhui University, Hefei, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ruibo","family":"Fu","sequence":"additional","affiliation":[{"name":"Institute of Automation, Chinese Academy of Sciences &amp; University of Chinese Academy of Sciences, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2022,10,10]]},"reference":[{"key":"e_1_3_2_2_1_1","first-page":"3989","volume-title":"INTERSPEECH","author":"Tao Jianhua","year":"2020","unstructured":"TaoWang, Jianhua Tao , Ruibo Fu , Jiangyan Yi , ZhengqiWen, and Chunyu Qiang . Bi-level speaker supervision for one-shot speech synthesis . In INTERSPEECH , pages 3989 -- 3993 , 2020 . TaoWang, Jianhua Tao, Ruibo Fu, Jiangyan Yi, ZhengqiWen, and Chunyu Qiang. Bi-level speaker supervision for one-shot speech synthesis. In INTERSPEECH, pages 3989--3993, 2020."},{"key":"e_1_3_2_2_2_1","doi-asserted-by":"publisher","DOI":"10.21437\/Interspeech.2017-1452"},{"key":"e_1_3_2_2_3_1","volume-title":"ICLR (Workshop)","author":"Sotelo Jose","year":"2017","unstructured":"Jose Sotelo , Soroush Mehri , Kundan Kumar , Jo\u00e3o Felipe Santos , Kyle Kastner , Aaron C Courville , and Yoshua Bengio . Char2wav : End-to-end speech synthesis . In ICLR (Workshop) , 2017 . Jose Sotelo, Soroush Mehri, Kundan Kumar, Jo\u00e3o Felipe Santos, Kyle Kastner, Aaron C Courville, and Yoshua Bengio. Char2wav: End-to-end speech synthesis. In ICLR (Workshop), 2017."},{"key":"e_1_3_2_2_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2019.8682804"},{"key":"e_1_3_2_2_5_1","first-page":"1654","volume-title":"Ruibo Fu. Half-Truth: A Partially Fake Audio Detection Dataset. In Proc. Interspeech 2021","author":"Yi Jiangyan","year":"2021","unstructured":"Jiangyan Yi , Ye Bai , Jianhua Tao , Haoxin Ma , Zhengkun Tian , Chenglong Wang , Tao Wang , and Ruibo Fu. Half-Truth: A Partially Fake Audio Detection Dataset. In Proc. Interspeech 2021 , pages 1654 -- 1658 , 2021 . Jiangyan Yi, Ye Bai, Jianhua Tao, Haoxin Ma, Zhengkun Tian, Chenglong Wang, Tao Wang, and Ruibo Fu. Half-Truth: A Partially Fake Audio Detection Dataset. In Proc. Interspeech 2021, pages 1654--1658, 2021."},{"key":"e_1_3_2_2_6_1","first-page":"886","volume-title":"Chenglong Wang. Continual Learning for Fake Audio Detection. In Proc. Interspeech 2021","author":"Ma Haoxin","year":"2021","unstructured":"Haoxin Ma , Jiangyan Yi , Jianhua Tao , Ye Bai , Zhengkun Tian , and Chenglong Wang. Continual Learning for Fake Audio Detection. In Proc. Interspeech 2021 , pages 886 -- 890 , 2021 . Haoxin Ma, Jiangyan Yi, Jianhua Tao, Ye Bai, Zhengkun Tian, and Chenglong Wang. Continual Learning for Fake Audio Detection. In Proc. Interspeech 2021, pages 886--890, 2021."},{"key":"e_1_3_2_2_7_1","volume-title":"Tomi Kinnunen, Nicholas Evans, et al. Asvspoof 2021: accelerating progress in spoofed and deepfake speech detection. arXiv preprint arXiv:2109.00537","author":"Yamagishi Junichi","year":"2021","unstructured":"Junichi Yamagishi , Xin Wang , Massimiliano Todisco , Md Sahidullah , Jose Patino , Andreas Nautsch , Xuechen Liu , Kong Aik Lee , Tomi Kinnunen, Nicholas Evans, et al. Asvspoof 2021: accelerating progress in spoofed and deepfake speech detection. arXiv preprint arXiv:2109.00537 , 2021 . Junichi Yamagishi, Xin Wang, Massimiliano Todisco, Md Sahidullah, Jose Patino, Andreas Nautsch, Xuechen Liu, Kong Aik Lee, Tomi Kinnunen, Nicholas Evans, et al. Asvspoof 2021: accelerating progress in spoofed and deepfake speech detection. arXiv preprint arXiv:2109.00537, 2021."},{"key":"e_1_3_2_2_8_1","doi-asserted-by":"publisher","DOI":"10.21437\/Interspeech.2019-2249"},{"key":"e_1_3_2_2_9_1","first-page":"2","volume-title":"Kong Aik Lee. The ASVspoof 2017 Challenge: Assessing the Limits of Replay Spoofing Attack Detection. In Proc. Interspeech 2017","author":"Kinnunen Tomi","year":"2017","unstructured":"Tomi Kinnunen , Md. Sahidullah , H\u00e9ctor Delgado , Massimiliano Todisco , Nicholas Evans , Junichi Yamagishi , and Kong Aik Lee. The ASVspoof 2017 Challenge: Assessing the Limits of Replay Spoofing Attack Detection. In Proc. Interspeech 2017 , pages 2 -- 6 , 2017 . Tomi Kinnunen, Md. Sahidullah, H\u00e9ctor Delgado, Massimiliano Todisco, Nicholas Evans, Junichi Yamagishi, and Kong Aik Lee. The ASVspoof 2017 Challenge: Assessing the Limits of Replay Spoofing Attack Detection. In Proc. Interspeech 2017, pages 2--6, 2017."},{"key":"e_1_3_2_2_10_1","volume-title":"Add 2022: the first audio deep synthesis detection challenge. arXiv preprint arXiv:2202.08433","author":"Yi Jiangyan","year":"2022","unstructured":"Jiangyan Yi , Ruibo Fu , Jianhua Tao , Shuai Nie , Haoxin Ma , Chenglong Wang , Tao Wang , Zhengkun Tian , Ye Bai , Cunhang Fan , Add 2022: the first audio deep synthesis detection challenge. arXiv preprint arXiv:2202.08433 , 2022 . Jiangyan Yi, Ruibo Fu, Jianhua Tao, Shuai Nie, Haoxin Ma, Chenglong Wang, Tao Wang, Zhengkun Tian, Ye Bai, Cunhang Fan, et al. Add 2022: the first audio deep synthesis detection challenge. arXiv preprint arXiv:2202.08433, 2022."},{"key":"e_1_3_2_2_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.csl.2017.01.001"},{"key":"e_1_3_2_2_12_1","doi-asserted-by":"publisher","DOI":"10.21437\/Interspeech.2015-472"},{"key":"e_1_3_2_2_13_1","doi-asserted-by":"publisher","DOI":"10.21437\/Interspeech.2021-847"},{"key":"e_1_3_2_2_14_1","volume-title":"The vicomtech audio deepfake detection system based on wav2vec2 for the 2022 add challenge. arXiv preprint arXiv:2203.01573","author":"Mart\u00edn-Do\u00f1as Juan M","year":"2022","unstructured":"Juan M Mart\u00edn-Do\u00f1as and Aitor \u00c1lvarez . The vicomtech audio deepfake detection system based on wav2vec2 for the 2022 add challenge. arXiv preprint arXiv:2203.01573 , 2022 . Juan M Mart\u00edn-Do\u00f1as and Aitor \u00c1lvarez. The vicomtech audio deepfake detection system based on wav2vec2 for the 2022 add challenge. arXiv preprint arXiv:2203.01573, 2022."},{"key":"e_1_3_2_2_15_1","first-page":"1013","volume-title":"Najim Dehak. ASSERT: Anti- Spoofing with Squeeze-Excitation and Residual Networks. In Proc. Interspeech 2019","author":"Lai I","year":"2019","unstructured":"Cheng- I Lai , Nanxin Chen , Jes\u00fas Villalba , and Najim Dehak. ASSERT: Anti- Spoofing with Squeeze-Excitation and Residual Networks. In Proc. Interspeech 2019 , pages 1013 -- 1017 , 2019 . Cheng-I Lai, Nanxin Chen, Jes\u00fas Villalba, and Najim Dehak. ASSERT: Anti- Spoofing with Squeeze-Excitation and Residual Networks. In Proc. Interspeech 2019, pages 1013--1017, 2019."},{"key":"e_1_3_2_2_16_1","doi-asserted-by":"publisher","DOI":"10.21437\/Interspeech.2019-3174"},{"key":"e_1_3_2_2_17_1","doi-asserted-by":"publisher","DOI":"10.21437\/Interspeech.2017-360"},{"key":"e_1_3_2_2_18_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"e_1_3_2_2_19_1","volume-title":"DARTS: differentiable architecture search. CoRR, abs\/1806.09055","author":"Liu Hanxiao","year":"2018","unstructured":"Hanxiao Liu , Karen Simonyan , and Yiming Yang . DARTS: differentiable architecture search. CoRR, abs\/1806.09055 , 2018 . Hanxiao Liu, Karen Simonyan, and Yiming Yang. DARTS: differentiable architecture search. CoRR, abs\/1806.09055, 2018."},{"key":"e_1_3_2_2_20_1","volume-title":"Partially-connected differentiable architecture search for deepfake and spoofing detection. arXiv preprint arXiv:2104.03123","author":"Ge Wanying","year":"2021","unstructured":"Wanying Ge , Michele Panariello , Jose Patino , Massimiliano Todisco , and Nicholas Evans . Partially-connected differentiable architecture search for deepfake and spoofing detection. arXiv preprint arXiv:2104.03123 , 2021 . Wanying Ge, Michele Panariello, Jose Patino, Massimiliano Todisco, and Nicholas Evans. Partially-connected differentiable architecture search for deepfake and spoofing detection. arXiv preprint arXiv:2104.03123, 2021."},{"key":"e_1_3_2_2_21_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2018.2833032"},{"key":"e_1_3_2_2_22_1","first-page":"12449","article-title":"A framework for self-supervised learning of speech representations","volume":"33","author":"Baevski Alexei","year":"2020","unstructured":"Alexei Baevski , Yuhao Zhou , Abdelrahman Mohamed , and Michael Auli . wav2vec 2.0 : A framework for self-supervised learning of speech representations . Advances in Neural Information Processing Systems , 33 : 12449 -- 12460 , 2020 . Alexei Baevski, Yuhao Zhou, Abdelrahman Mohamed, and Michael Auli. wav2vec 2.0: A framework for self-supervised learning of speech representations. Advances in Neural Information Processing Systems, 33:12449--12460, 2020.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_2_23_1","doi-asserted-by":"publisher","DOI":"10.21437\/Interspeech.2019-1873"},{"key":"e_1_3_2_2_24_1","volume-title":"Hubert: Self-supervised speech representation learning by masked prediction of hidden units","author":"Hsu Wei-Ning","year":"2021","unstructured":"Wei-Ning Hsu , Benjamin Bolte , Yao-Hung Hubert Tsai , Kushal Lakhotia, Ruslan Salakhutdinov, and Abdelrahman Mohamed. Hubert: Self-supervised speech representation learning by masked prediction of hidden units . IEEE\/ACM Transactions on Audio, Speech, and Language Processing , 29:3451--3460, 2021 . Wei-Ning Hsu, Benjamin Bolte, Yao-Hung Hubert Tsai, Kushal Lakhotia, Ruslan Salakhutdinov, and Abdelrahman Mohamed. Hubert: Self-supervised speech representation learning by masked prediction of hidden units. IEEE\/ACM Transactions on Audio, Speech, and Language Processing, 29:3451--3460, 2021."},{"key":"e_1_3_2_2_25_1","volume-title":"Exploring wav2vec 2.0 on speaker verification and language identification. arXiv preprint arXiv:2012.06185","author":"Fan Zhiyun","year":"2020","unstructured":"Zhiyun Fan , Meng Li , Shiyu Zhou , and Bo Xu . Exploring wav2vec 2.0 on speaker verification and language identification. arXiv preprint arXiv:2012.06185 , 2020 . Zhiyun Fan, Meng Li, Shiyu Zhou, and Bo Xu. Exploring wav2vec 2.0 on speaker verification and language identification. arXiv preprint arXiv:2012.06185, 2020."},{"key":"e_1_3_2_2_26_1","volume-title":"Emotion recognition from speech using wav2vec 2.0 embeddings. arXiv preprint arXiv:2104.03502","author":"Pepino Leonardo","year":"2021","unstructured":"Leonardo Pepino , Pablo Riera , and Luciana Ferrer . Emotion recognition from speech using wav2vec 2.0 embeddings. arXiv preprint arXiv:2104.03502 , 2021 . Leonardo Pepino, Pablo Riera, and Luciana Ferrer. Emotion recognition from speech using wav2vec 2.0 embeddings. arXiv preprint arXiv:2104.03502, 2021."},{"key":"e_1_3_2_2_27_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP43922.2022.9747605"},{"key":"e_1_3_2_2_28_1","volume-title":"Investigating self-supervised front ends for speech spoofing countermeasures. arXiv preprint arXiv:2111.07725","author":"Wang Xin","year":"2021","unstructured":"Xin Wang and Junichi Yamagishi . Investigating self-supervised front ends for speech spoofing countermeasures. arXiv preprint arXiv:2111.07725 , 2021 . Xin Wang and Junichi Yamagishi. Investigating self-supervised front ends for speech spoofing countermeasures. arXiv preprint arXiv:2111.07725, 2021."},{"key":"e_1_3_2_2_29_1","volume-title":"Categorical reparameterization with gumbel-softmax. stat, 1050:5","author":"Jang Eric","year":"2017","unstructured":"Eric Jang , Shixiang Gu , and Ben Poole . Categorical reparameterization with gumbel-softmax. stat, 1050:5 , 2017 . Eric Jang, Shixiang Gu, and Ben Poole. Categorical reparameterization with gumbel-softmax. stat, 1050:5, 2017."},{"key":"e_1_3_2_2_30_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2015.7178964"},{"key":"e_1_3_2_2_31_1","first-page":"4279","volume-title":"Pengyuan Zhang. The Effect of Silence and Dual-Band Fusion in Anti-Spoofing System. In Proc. Interspeech 2021","author":"Zhang Yuxiang","year":"2021","unstructured":"Yuxiang Zhang , Wenchao Wang , and Pengyuan Zhang. The Effect of Silence and Dual-Band Fusion in Anti-Spoofing System. In Proc. Interspeech 2021 , pages 4279 -- 4283 , 2021 . Yuxiang Zhang, Wenchao Wang, and Pengyuan Zhang. The Effect of Silence and Dual-Band Fusion in Anti-Spoofing System. In Proc. Interspeech 2021, pages 4279--4283, 2021."},{"key":"e_1_3_2_2_32_1","doi-asserted-by":"publisher","DOI":"10.21437\/Interspeech.2021-1404"},{"key":"e_1_3_2_2_33_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP39728.2021.9414234"},{"key":"e_1_3_2_2_34_1","volume-title":"Visualizing data using t-sne. Journal of machine learning research, 9(11)","author":"der Maaten Laurens Van","year":"2008","unstructured":"Laurens Van der Maaten and Geoffrey Hinton . Visualizing data using t-sne. Journal of machine learning research, 9(11) , 2008 . Laurens Van der Maaten and Geoffrey Hinton. Visualizing data using t-sne. Journal of machine learning research, 9(11), 2008."}],"event":{"name":"MM '22: The 30th ACM International Conference on Multimedia","location":"Lisboa Portugal","acronym":"MM '22","sponsor":["SIGMM ACM Special Interest Group on Multimedia"]},"container-title":["Proceedings of the 1st International Workshop on Deepfake Detection for Audio Multimedia"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3552466.3556530","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3552466.3556530","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T17:49:25Z","timestamp":1750182565000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3552466.3556530"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,10,10]]},"references-count":34,"alternative-id":["10.1145\/3552466.3556530","10.1145\/3552466"],"URL":"https:\/\/doi.org\/10.1145\/3552466.3556530","relation":{},"subject":[],"published":{"date-parts":[[2022,10,10]]},"assertion":[{"value":"2022-10-10","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}