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陈家源 等: 说话人信息引导的高性能音频对抗攻击                                                        3047


                     perturbations. In: Proc. of the 2020 ACM SIGSAC Conf. on Computer and Communications Security. ACM, 2020. 1121–1134. [doi: 10.
                     1145/3372297.3423348]
                 [17]   Lin YQ, Abdulla WH. Principles of psychoacoustics. In: Lin YQ, Abdulla WH, eds. Audio Watermark: A Comprehensive Foundation
                     Using Matlab. Cham: Springer, 2015. 15–49. [doi: 10.1007/978-3-319-07974-5_2]
                 [18]   Xie CH, Zhang ZS, Zhou YY, Bai S, Wang JY, Ren Z, Yuille AL. Improving transferability of adversarial examples with input diversity.
                     In: Proc. of the 2019 IEEE/CVF Conf. on Computer Vision and Pattern Recognition. Long Beach: IEEE, 2019. 2725–2734. [doi: 10.1109/
                     CVPR.2019.00284]
                 [19]   Chen GK, Zhang YD, Zhao Z, Song F. QFA2SR: Query-free adversarial transfer attacks to speaker recognition systems. In: Proc. of the
                     32nd USENIX Security Symp. Anaheim: USENIX Association, 2023. 2437–2454.
                 [20]   Zhang Y, Li HW, Xu GW, Luo XZ, Dong GS. Generating audio adversarial examples with ensemble substituted models. In: Proc. of the
                     2021 IEEE Int’l Conf. on Communications. Montreal: IEEE, 2021. 1–6. [doi: 10.1109/ICC42927.2021.9500431]
                 [21]   Xue M, Peng K, Gong XL, Zhang Q, Chen YJ, Li RT. Echo: Reverberation-based fast black-box adversarial attacks on intelligent audio
                     systems. Proc. of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 2023, 7(3): 137. [doi: 10.1145/3610874]
                 [22]   Reynolds DA, Quatieri TF, Dunn RB. Speaker verification using adapted Gaussian mixture models. Digital Signal Processing, 2000,
                     10(1–3): 19–41. [doi: 10.1006/dspr.1999.0361]
                 [23]   Dehak N, Dehak R, Kenny P, Brümmer N, Ouellet P, Dumouchel P. Support vector machines versus fast scoring in the low-dimensional
                     total  variability  space  for  speaker  verification.  In:  Proc.  of  the  10th  Annual  Conf.  of  the  Int’l  Speech  Communication  Association.
                     Brighton: ISCA, 2009. 1559–1562.
                 [24]   Variani E, Lei X, McDermott E, Moreno IL, Gonzalez-Dominguez J. Deep neural networks for small footprint text-dependent speaker
                     verification. In: Proc. of the 2014 IEEE Int’l Conf. on Acoustics, Speech and Signal Processing. Florence: IEEE, 2014. 4052–4056. [doi:
                     10.1109/ICASSP.2014.6854363]
                 [25]   Snyder D, Garcia-Romero D, Sell G, Povey D, Khudanpur S. X-vectors: Robust DNN embeddings for speaker recognition. In: Proc. of
                     the 2018 IEEE Int’l Conf. on Acoustics, Speech and Signal Processing. Calgary: IEEE, 2018. 5329–5333. [doi: 10.1109/ICASSP.2018.
                     8461375]
                 [26]   Chen GK, Zhao Z, Song F, Chen S, Fan LL, Liu Y. AS2T: Arbitrary source-to-target adversarial attack on speaker recognition systems.
                     IEEE Trans. on Dependable and Secure Computing, 2022: 1–17. [doi: 10.1109/TDSC.2022.3189397]
                 [27]   Li JY, Tu WP, Xiao L. FreeVC: Towards high-quality text-free one-shot voice conversion. In: Proc. of the 2023 IEEE Int’l Conf. on
                     Acoustics, Speech and Signal Processing. Rhodes Island: IEEE, 2023. 1–5. [doi: 10.1109/ICASSP49357.2023.10095191]
                 [28]   Liu SX, Cao YW, Wang DS, Wu XX, Liu XY, Meng HL. Any-to-many voice conversion with location-relative sequence-to-sequence
                     modeling. IEEE/ACM Trans. on Audio, Speech, and Language Processing, 2021, 29: 1717–1728. [doi: 10.1109/TASLP.2021.3076867]
                 [29]   Kim J, Kong J, Son J. Conditional variational autoencoder with adversarial learning for end-to-end text-to-speech. In: Proc. of the 38th Int’l
                     Conf. on Machine Learning. PMLR, 2021. 5530–5540.
                 [30]   Panayotov V, Chen GG, Povey D, Khudanpur S. LibriSpeech: An ASR corpus based on public domain audio books. In: Proc. of the 2015
                     IEEE Int’l Conf. on Acoustics, Speech and Signal Processing. South Brisbane: IEEE, 2015. 5206–5210. [doi: 10.1109/ICASSP.2015.
                     7178964]
                 [31]   Wu ZZ, Khodabakhsh A, Demiroglu C, Yamagishi J, Saito D, Toda T, King S. SAS: A speaker verification spoofing database containing
                     diverse  attacks.  In:  Proc.  of  the  2015  IEEE  Int’l  Conf.  on  Acoustics,  Speech  and  Signal  Processing.  South  Brisbane:  IEEE,  2015.
                     4440–4444. [doi: 10.1109/ICASSP.2015.7178810]
                 [32]   Chen GK, Zhao Z, Song F, Chen S, Fan LL, Wang F, Wang J. Towards understanding and mitigating audio adversarial examples for
                     speaker recognition. IEEE Trans. on Dependable and Secure Computing, 2023, 20(5): 3970–3987. [doi: 10.1109/TDSC.2022.3220673]
                 [33]   KALDI. VoxCeleb Models. 2022. https://kaldi-asr.org/models/m7
                 [34]   KALDI. SITW Models. 2022. https://kaldi-asr.org/models/m8
                 [35]   Desplanques  B,  Thienpondt  J,  Demuynck  K.  ECAPA-TDNN:  Emphasized  channel  attention,  propagation  and  aggregation  in  TDNN
                     based speaker verification. In: Proc. of the 21st Annual Conf. of the Int’l Speech Communication Association. Shanghai: ISCA, 2020.
                     3830–3834.
                 [36]   Faundez-Zanuy M, Monte-Moreno E. State-of-the-art in speaker recognition. IEEE Aerospace and Electronic Systems Magazine, 2005,
                     20(5): 7–12. [doi: 10.1109/MAES.2005.1432568]
                 [37]   Tencent Cloud. Tencent automatic speech recognition. 2025 (in Chinese). https://cloud.tencent.com/product/asr
                 [38]   IFlytek. IFlytek voiceprint recognition. 2025 (in Chinese). https://www.xfyun.cn/services/voiceprint-recognition
                 [39]   Unisound. Unisound voiceprint recognition. 2025 (in Chinese). https://ai-poc.hivoice.cn/voiceprint-recognition
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