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Adversarial examples are inputs to machine learning models designed by an adversary to cause an incorrect output.
Image method for efficiently simulating small-room acoustics
Allen, J. B. and Berkley, D. A · 1979
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Introduction to digital audio coding and standards
Mitchell, J. L · 2004
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Evasion attacks against machine learning at test time
Biggio, B., Corona, I., Maiorca, D., Nelson, B., Šrndić, N., Laskov, P., Giacinto, G., and Roli, F · 2013
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Intriguing properties of neural networks
Szegedy, C., Zaremba, W., Sutskever, I., Bruna, J., Erhan, D., Goodfellow, I., and Fergus, R · 2013
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Neural machine translation by jointly learning to align and translate
Bahdanau, D., Cho, K., and Bengio, Y · 2014
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Adam: A method for stochastic optimization
Kingma, D. P. and Ba, J · 2014
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Sequence to sequence learning with neural networks
Sutskever, I., Vinyals, O., and Le, Q. V · 2014
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Principles of psychoacoustics
Lin, Y. and Abdulla, W. H · 2015
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Librispeech: an asr corpus based on public domain audio books
Panayotov, V., Chen, G., Povey, D., and Khudanpur, S · 2015
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Hidden voice commands
Carlini, N., Mishra, P., Vaidya, T., Zhang, Y., Sherr, M., Shields, C., Wagner, D., and Zhou, W · 2016
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Listen, attend and spell: A neural network for large vocabulary conversational speech recognition
Chan, W., Jaitly, N., Le, Q., and Vinyals, O · 2016
Cited alongside, same era.
Adversarial examples in the physical world
Kurakin, A., Goodfellow, I., and Bengio, S · 2016
Cited alongside, same era.
Towards evaluating the robustness of neural networks
Carlini, N. and Wagner, D · 2017
Cited alongside, same era.
Houdini: Fooling deep structured prediction models
Cisse, M., Adi, Y., Neverova, N., and Keshet, J · 2017
Cited alongside, same era.
Crafting adversarial examples for speech paralinguistics applications
Gong, Y. and Poellabauer, C · 2017
Cited alongside, same era.
Synthesizing robust adversarial examples
Athalye, A., Engstrom, L., Ilyas, A., and Kwok, K · 2018
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Audio adversarial examples: Targeted attacks on speech-to-text
Carlini, N. and Wagner, D. A · 2018
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Khare, S., Aralikatte, R., and Mani, S · 2018
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Pyroomacoustics: A python package for audio room simulation and array processing algorithms
Scheibler, R., Bezzam, E., and Dokmanić, I · 2018
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Adversarial attacks against automatic speech recognition systems via psychoacoustic hiding
Schönherr, L., Kohls, K., Zeiler, S., Holz, T., and Kolossa, D · 2018
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Adversarial attacks on neural network policies
Huang, S., Papernot, N., Goodfellow, I., Duan, Y., and Abbeel, P · 2017
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Adversarial examples for evaluating reading comprehension systems
Jia, R. and Liang, P · 2017
Cited alongside, same era.
Towards deep learning models resistant to adversarial attacks
Madry, A., Makelov, A., Schmidt, L., Tsipras, D., and Vladu, A · 2017
Cited alongside, same era.
Song, L. and Mittal, P · 2017
Cited alongside, same era.
Dolphinattack: Inaudible voice commands
Zhang, G., Yan, C., Ji, X., Zhang, T., Zhang, T., and Xu, W · 2017
Cited alongside, same era.
Taori, R., Kamsetty, A., Chu, B., and Vemuri, N · 2018
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Robust audio adversarial example for a physical attack
Yakura, H. and Sakuma, J · 2018
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Commandersong: A systematic approach for practical adversarial voice recognition
Yuan, X., Chen, Y., Zhao, Y., Long, Y., Liu, X., Chen, K., Zhang, S., Huang, H., Wang, X., and Gunter, C. A · 2018
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Lingvo: a modular and scalable framework for sequence-to-sequence modeling
Shen, J., Nguyen, P., Wu, Y., Chen, Z., Chen, M. X., Jia, Y., Kannan, A., Sainath, T., Cao, Y., Chiu, C.-C., et al · 2019
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