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However, Commercial ASR solutions are typically \u201cone-size-fits-all\u201d products and clients are inevitably faced with the risk of severe performance degradation in field test. Meanwhile, with new data regulations such as the European Union\u2019s General Data Protection Regulation (GDPR) coming into force, ASR vendors, which traditionally utilize the speech training data in a centralized approach, are becoming increasingly helpless to solve this problem, since accessing clients\u2019 speech data is prohibited. Here, we show that by seamlessly integrating three machine learning paradigms (i.e.,\n            <jats:bold>T<\/jats:bold>\n            ransfer learning,\n            <jats:bold>F<\/jats:bold>\n            ederated learning, and\n            <jats:bold>E<\/jats:bold>\n            volutionary learning (TFE)), we can successfully build a win-win ecosystem for ASR clients and vendors and solve all the aforementioned problems plaguing them. Through large-scale quantitative experiments, we show that with TFE, the clients can enjoy far better ASR solutions than the \u201cone-size-fits-all\u201d counterpart, and the vendors can exploit the abundance of clients\u2019 data to effectively refine their own ASR products.\n          <\/jats:p>","DOI":"10.1145\/3447687","type":"journal-article","created":{"date-parts":[[2021,5,6]],"date-time":"2021-05-06T06:08:22Z","timestamp":1620281302000},"page":"1-19","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":10,"title":["A GDPR-compliant Ecosystem for Speech Recognition with Transfer, Federated, and Evolutionary Learning"],"prefix":"10.1145","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2309-1809","authenticated-orcid":false,"given":"Di","family":"Jiang","sequence":"first","affiliation":[{"name":"AI Group, WeBank Co., Ltd., Shenzhen, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3993-4751","authenticated-orcid":false,"given":"Conghui","family":"Tan","sequence":"additional","affiliation":[{"name":"AI Group, WeBank Co., Ltd., Shenzhen, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jinhua","family":"Peng","sequence":"additional","affiliation":[{"name":"AI Group, WeBank Co., Ltd., Shenzhen, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chaotao","family":"Chen","sequence":"additional","affiliation":[{"name":"AI Group, WeBank Co., Ltd., Shenzhen, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xueyang","family":"Wu","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, The Hong Kong University of Science and Technology, Kowloon, Hong Kong"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Weiwei","family":"Zhao","sequence":"additional","affiliation":[{"name":"AI Group, WeBank Co., Ltd., Shenzhen, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuanfeng","family":"Song","sequence":"additional","affiliation":[{"name":"AI Group, WeBank Co., Ltd., Shenzhen, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5598-0312","authenticated-orcid":false,"given":"Yongxin","family":"Tong","sequence":"additional","affiliation":[{"name":"BDBC, SKLSDE Lab and IRI, Beihang University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chang","family":"Liu","sequence":"additional","affiliation":[{"name":"AI Group, WeBank Co., Ltd., Shenzhen, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qian","family":"Xu","sequence":"additional","affiliation":[{"name":"AI Group, WeBank Co., Ltd., Shenzhen, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qiang","family":"Yang","sequence":"additional","affiliation":[{"name":"AI Group, WeBank Co., Ltd., China and Department of Computer Science and Engineering, Hong Kong University of Science and Technology, Kowloon, Hong Kong"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Li","family":"Deng","sequence":"additional","affiliation":[{"name":"Citadel LLC, Chicago, IL, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2021,5,5]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/2976749.2978318"},{"key":"e_1_2_1_2_1","volume-title":"Proceedings of the European Conference on Speech Communication and Technology (Eurospeech\u201995)","author":"Abrash Victor","year":"1995","unstructured":"Victor Abrash , Horacio Franco , Ananth Sankar , and Michael Cohen . 1995 . 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Yan Huang, Dong Yu, Chaojun Liu, and Yifan Gong. 2014. Multi-accent deep neural network acoustic model with accent-specific top layer using the KLD-regularized model adaptation. 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Retrieved from https:\/\/arXiv:1602.05629."},{"key":"e_1_2_1_47_1","doi-asserted-by":"publisher","DOI":"10.21437\/Interspeech.2010-343"},{"key":"e_1_2_1_48_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2011.5947611"},{"key":"e_1_2_1_49_1","doi-asserted-by":"publisher","DOI":"10.5555\/2999792.2999959"},{"key":"e_1_2_1_50_1","doi-asserted-by":"publisher","DOI":"10.5555\/1623755.1623876"},{"key":"e_1_2_1_51_1","volume-title":"Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS\u201905)","volume":"5","author":"Morin Frederic","year":"2005","unstructured":"Frederic Morin and Yoshua Bengio . 2005 . Hierarchical probabilistic neural network language model . In Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS\u201905) , Vol. 5 . Citeseer, 246\u2013252. Frederic Morin and Yoshua Bengio. 2005. Hierarchical probabilistic neural network language model. In Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS\u201905), Vol. 5. Citeseer, 246\u2013252."},{"key":"e_1_2_1_52_1","volume-title":"Proceedings of the European Conference on Speech Communication and Technology (Eurospeech\u201995)","author":"Neto Joao","year":"1995","unstructured":"Joao Neto , Lu\u00eds Almeida , Mike Hochberg , Ciro Martins , Luis Nunes , Steve Renals , and Tony Robinson . 1995 . Speaker-adaptation for hybrid HMM-ANN continuous speech recognition system . In Proceedings of the European Conference on Speech Communication and Technology (Eurospeech\u201995) . 2171\u20132174. Joao Neto, Lu\u00eds Almeida, Mike Hochberg, Ciro Martins, Luis Nunes, Steve Renals, and Tony Robinson. 1995. Speaker-adaptation for hybrid HMM-ANN continuous speech recognition system. In Proceedings of the European Conference on Speech Communication and Technology (Eurospeech\u201995). 2171\u20132174."},{"key":"e_1_2_1_53_1","doi-asserted-by":"publisher","DOI":"10.1007\/s40747-017-0036-x"},{"key":"e_1_2_1_54_1","doi-asserted-by":"publisher","DOI":"10.1109\/TEVC.2013.2248159"},{"key":"e_1_2_1_55_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2009.191"},{"key":"e_1_2_1_56_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2009.191"},{"key":"e_1_2_1_57_1","unstructured":"Nicolas Papernot Mart\u00edn Abadi Ulfar Erlingsson Ian Goodfellow and Kunal Talwar. 2016. Semi-supervised knowledge transfer for deep learning from private training data. Retrieved from https:\/\/arXiv:1610.05755.  Nicolas Papernot Mart\u00edn Abadi Ulfar Erlingsson Ian Goodfellow and Kunal Talwar. 2016. Semi-supervised knowledge transfer for deep learning from private training data. Retrieved from https:\/\/arXiv:1610.05755."},{"key":"e_1_2_1_58_1","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/D14-1162"},{"key":"e_1_2_1_59_1","volume-title":"Proceedings of the IEEE Workshop on Automatic Speech Recognition and Understanding. IEEE Signal Processing Society.","author":"Povey Daniel","year":"2011","unstructured":"Daniel Povey , Arnab Ghoshal , Gilles Boulianne , Lukas Burget , Ondrej Glembek , Nagendra Goel , Mirko Hannemann , Petr Motlicek , Yanmin Qian , Petr Schwarz , et\u00a0al. 2011 . The Kaldi speech recognition toolkit . In Proceedings of the IEEE Workshop on Automatic Speech Recognition and Understanding. IEEE Signal Processing Society. Daniel Povey, Arnab Ghoshal, Gilles Boulianne, Lukas Burget, Ondrej Glembek, Nagendra Goel, Mirko Hannemann, Petr Motlicek, Yanmin Qian, Petr Schwarz, et\u00a0al. 2011. The Kaldi speech recognition toolkit. In Proceedings of the IEEE Workshop on Automatic Speech Recognition and Understanding. IEEE Signal Processing Society."},{"key":"e_1_2_1_60_1","volume-title":"Le","author":"Real Esteban","year":"2018","unstructured":"Esteban Real , Alok Aggarwal , Yanping Huang , and Quoc V . Le . 2018 . Regularized evolution for image classifier architecture search. Retrieved from https:\/\/arXiv:1802.01548. Esteban Real, Alok Aggarwal, Yanping Huang, and Quoc V. Le. 2018. Regularized evolution for image classifier architecture search. Retrieved from https:\/\/arXiv:1802.01548."},{"key":"e_1_2_1_61_1","doi-asserted-by":"publisher","DOI":"10.5555\/3305890.3305981"},{"key":"e_1_2_1_62_1","first-page":"169","article-title":"On data banks and privacy homomorphisms","volume":"4","author":"Rivest Ronald L.","year":"1978","unstructured":"Ronald L. Rivest , Len Adleman , Michael L. Dertouzos , et\u00a0al. 1978 . On data banks and privacy homomorphisms . Found. Secure Comput. 4 , 11 (1978), 169 \u2013 180 . Ronald L. Rivest, Len Adleman, Michael L. Dertouzos, et\u00a0al. 1978. 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Differentially private hypothesis transfer learning . In Proceedings of the Joint European Conference on Machine Learning and Knowledge Discovery in Databases. Springer, 811\u2013826 . Yang Wang, Quanquan Gu, and Donald Brown. 2018. Differentially private hypothesis transfer learning. In Proceedings of the Joint European Conference on Machine Learning and Knowledge Discovery in Databases. 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Multimodal intelligence: Representation learning information fusion and applications. Retrieved from https:\/\/arXiv:1911.03977.  Chao Zhang Zichao Yang Xiaodong He and Li Deng. 2019. Multimodal intelligence: Representation learning information fusion and applications. Retrieved from https:\/\/arXiv:1911.03977."},{"key":"e_1_2_1_84_1","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2019.2919699"},{"key":"e_1_2_1_85_1","doi-asserted-by":"crossref","unstructured":"Yuze Zou Shaohan Feng Dusit Niyato Yutao Jiao Shimin Gong and Wenqing Cheng. 2019. Mobile device training strategies in federated learning: An evolutionary game approach. In Proceedings of the International Conference on Internet of Things (iThings\u201919) and IEEE Green Computing and Communications (GreenCom\u201919) and IEEE Cyber Physical and Social Computing (CPSCom\u201919) and IEEE Smart Data (SmartData\u201919). IEEE 874\u2013879.  Yuze Zou Shaohan Feng Dusit Niyato Yutao Jiao Shimin Gong and Wenqing Cheng. 2019. Mobile device training strategies in federated learning: An evolutionary game approach. In Proceedings of the International Conference on Internet of Things (iThings\u201919) and IEEE Green Computing and Communications (GreenCom\u201919) and IEEE Cyber Physical and Social Computing (CPSCom\u201919) and IEEE Smart Data (SmartData\u201919). 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