Papers to Read on Adversarial Examples for Speech Data

Adversarial Attacks

1. Audio Adversarial Examples: Targeted Attacks on Speech-to-Text. Nicholas Carlini and David Wagner. IEEE Security and Privacy Workshops. 2018 [White-Box-Attack] [Targeted] [cite]

2. Robust Audio Adversarial Example for a Physical Attack. Hiromu Yakura and Jun Sakuma. Twenty-Eighth International Joint Conference on Artificial Intelligence, (IJCAI). 2019 [White-Box-Attack] [Targeted] [cite]

3. Adversarial Black-Box Attacks on Automatic Speech Recognition Systems Using Multi-Objective Evolutionary Optimization. Shreya Khare, Rahul Aralikatte and Senthil Mani. 20th Annual Conference of the International Speech Communication Association. 2019 [Black-Box-Attack] [Targeted] [cite]

4. Imperceptible, Robust, and Targeted Adversarial Examples for Automatic Speech Recognition. Yao Qin, Nicholas Carlini, Garrison W. Cottrell, Ian J. Goodfellow and Colin Raffel. 36th International Conference on Machine Learning, (ICML). 2019 [White-Box-Attack] [Targeted] [cite]

5. Universal Adversarial Perturbations for Speech Recognition Systems. Paarth Neekhara, Shehzeen Hussain, Prakhar Pandey, Shlomo Dubnov, Julian J. McAuley, Farinaz Koushanfar. Interspeech 2019, 20th Annual Conference of the International Speech Communication Association. 2019 [White-Box-Attack] [Untargeted] [cite]

6. Enabling Fast and Universal Audio Adversarial Attack Using Generative Model. Yi Xie, Zhuohang Li, Cong Shi, Jian Liu, Yingying Chen, Bo Yuanl. arXiv 2020 [White-Box-Attack] [Targeted and Untargeted] [cite]

7. Defending Your Voice: Adversarial Attack on Voice Conversion. Chien-yu Huang, Yist Y. Lin, Hung-yi Lee, Lin-shan Lee . arXiv. [White-Box-Attack] [Untargeted] [cite]

8. Fooling End-to-end Speaker Verification by Adversarial Examples. Felix Kreuk, Yossi Adi, Moustapha Ciss{'{e}}, Joseph Keshet 19th Annual Conference of the International Speech Communication Association. 2018 [White-Box-Attack] [Targeted] [cite]

9. Universal Adversarial Attacks On Spoken Language Assessment Systems. Vyas Raina, Mark J. F. Gales, Kate Knill. INTERSPEECH. 2020 [Black-Box-Attack] [Untargeted] [cite]

Adversarial Defense

1. Training Augmentation with Adversarial Examples for Robust Speech Recognition. Sining Sun, Ching-Feng Yeh, Mari Ostendorf, Mei-Yuh Hwang and Lei Xie. 19th Annual Conference of the International Speech Communication Association. 2018 [Adversarial Training] [cite]

2. Isolated and Ensemble Audio Preprocessing Methods for Detecting Adversarial Examples against Automatic Speech Recognition. Krishan Rajaratnam, Kunal Shah and Jugal Kalita. 30th Conference on Computational Linguistics and Speech Processing, (ROCLING). 2019 [Precprocessing] [cite]

3. Characterizing Audio Adversarial Examples Using Temporal Dependency. Zhuolin Yang, Bo Li, Pin-Yu Chen and Dawn Song. 7th International Conference on Learning Representations, (ICLR). 2019 [Precprocessing] [cite]

4. Characterizing Speech Adversarial Examples Using Self-Attention U-Net Enhancement. Chao-Han Huck Yang, Jun Qi, Pin-Yu Chen, Xiaoli Ma and Chin-Hui Lee. 45th International Conference on Acoustics, Speech, and Signal Processing (ICASSP). 2020 [Precprocessing] [cite]

5. Detecting Adversarial Attacks On Audio-Visual Speech Recognition. Pingchuan Ma, Stavros Petridis, Maja Pantic. arXiv. 2019 [Detection] [cite]

6. Detecting Audio Attacks on {ASR} Systems with Dropout Uncertainty. Tejas Jayashankar, Jonathan Le Roux, Pierre Moulin. arXiv. 2020 [Detection] [cite]

7. MP3 Compression To Diminish Adversarial Noise in End-to-End Speech Recognition. Iustina Andronic, Ludwig K{"{u}}rzinger, Edgar Ricardo Chavez Rosas, Gerhard Rigoll, Bernhard U. Seeber. 22nd International Conference on Speech and Computer(SPECOM). 2020 [Processing] [cite]

8. Defense against adversarial attacks on spoofing countermeasures of ASV. Haibin Wu, Songxiang Liu, Helen Meng, Hung-yi Lee . 45th International Conference on Acoustics, Speech, and Signal Processing (ICASSP). 2020 [Preprocessing and Adversarial Training] [cite]

9. Adversarial Regularization for End-to-End Robust Speaker Verification. Qing Wang, Pengcheng Guo, Sining Sun, Lei Xie, John H. L. Hansen . 20th Annual Conference of the International Speech Communication Association. 2019 [Adversarial Training] [cite]

10. Adversarial Examples for Improving End-to-end Attention-based Small-footprint Keyword Spotting . Xiong Wang, Sining Sun, Changhao Shan, Jingyong Hou, Lei Xie, Shen Li, Xin Lei . 45th International Conference on Acoustics, Speech, and Signal Processing (ICASSP). 2019 [Adversarial Training] [cite]

11. Investigating Robustness of Adversarial Samples Detection for Automatic Speaker Verification . Xu Li, Na Li, Jinghua Zhong, Xixin Wu, Xunying Liu, Dan Su, Dong Yu, Helen Meng . INTERSPEECH. 2020 [Detection (Network)] [cite]

12. Speaker Identification for Household Scenarios with Self-attention and Adversarial Training . Ruirui Li, Jyun-Yu Jiang, Xian Wu, Chu-Cheng Hsieh, Andreas Stolcke . INTERSPEECH. 2020 [ Adversarial Training ] [cite]