［1］张琳琳, 李晓伟. 大力开展数据安全合规性评估为数字经济发展保驾护航［J］. 信息安全与通信保密, 2021, 11(4): 8490［2］陈磊. 隐私合规视角下数据安全建设的思考与实践［J］. 保密科学技术, 2020, 10(4): 3946［3］张纾婷. 数据安全在我国互联网企业合规计划中的构建［J］. 特区经济, 2024 (1): 128132［4］孙婧. 面向Android应用的第三方库隐私合规性检测设计与实现［D］. 北京: 北京邮电大学, 2021［5］CSDN. 敏感数据识别［EBOL］. ［20230506］. https:blog.csdn.netm0_37482190articledetails130522547［6］张权. 基于人工智能的消费者隐私数据保护刍议［J］. 科技与创新, 2023 (5): 4648［7］Mikolov T, Chen K, Corrado G, et al. Efficient estimation of word representations invector space［J］. arXiv preprint, arXiv: 1301.3781v3, 2013［8］Vaswani A, Shazeer N, Parmar N, et al. Attention is all you need［J］. arXiv preprint, arXiv: 1706.03762, 2017［9］王澳回, 张珑, 宋文宇, 等. 端到端流式语音识别研究综述［J］. 计算机工程与应用, 2023, 59(2): 2233［10］王绮宇, 龙云璐. 基于手机的语音识别模型专利技术综述［J］. 中国科技信息, 2021 (3): 1718［11］Radford A, Kim J W, Xu T, et al. Robust speech recognition via largescale weak supervision［J］. arXiv preprint, arXiv: 2212.04356v1, 2022［12］GITHUB. The Illustrated image captioning using transformers［EBOL］. ［20221120］. https:ankur3107.github.ioblogstheillustratedimagecaptioningusingtransformers［13］Dosovitskiy A, Beyer L, Kolesnikov A, et al. An image is worth 16×16 words: Transformers for image recognition at scale［C］ Proc of Int Conf on Learning Representation. Piscataway, NJ: IEEE, 2021［14］Huang Zhiheng, Xu Wei, Yu Kai. Bidirectional LSTMCRF models for sequence tagging［J］. arXiv preprint, arXiv: 1508.01991v1, 2015［15］Jacob Devlin, Mingwei Chang, Kenton Lee, et al. BERT: Pretraining of deep bidirectional transformers for language understanding［J］. arXiv preprint, arXiv: 1810.04805v2, 2019
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