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It is perhaps no longer surprising that machine learning models, especially deep neural networks, are particularly vulnerable to attacks.
Timit acoustic phonetic continuous speech corpus
John S Garofolo · 1993
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Testing with the yoho cd-rom voice verification corpus
Joseph P Campbell · 1995
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Unsupervised feature learning for audio classification using convolutional deep belief networks
Honglak Lee, Peter Pham, Yan Largman, and Andrew Ng · 2009
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Intriguing properties of neural networks
Christian Szegedy, Wojciech Zaremba, Ilya Sutskever, Joan Bruna, Dumitru Erhan, Ian Goodfellow, and Rob Fergus · 2013
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Evasion attacks against machine learning at test time
Battista Biggio, Igino Corona, Davide Maiorca, Blaine Nelson, Nedim Šrndić, Pavel Laskov, Giorgio Giacinto, and Fabio Roli · 2013
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Deep inside convolutional networks: Visualising image classification models and saliency maps
Karen Simonyan, Andrea Vedaldi, and Andrew Zisserman · 2013
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Visualizing and understanding convolutional networks
Matthew D Zeiler and Rob Fergus · 2014
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Recommending music on spotify with deep learning
Sander Dieleman · 2014
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End-to-end learning for music audio
S. Dieleman and B. Schrauwen · 2014
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Understanding neural networks through deep visualization
Jason Yosinski, Jeff Clune, Thomas Fuchs, and Hod Lipson · 2015
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Distilling the knowledge in a neural network
Geoffrey E. Hinton, Oriol Vinyals, and Jeffrey Dean · 2015
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librosa: Audio and music signal analysis in python
Brian McFee, Colin Raffel, Dawen Liang, Daniel PW Ellis, Matt McVicar, Eric Battenberg, and Oriol Nieto · 2015
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Librispeech: an asr corpus based on public domain audio books
Vassil Panayotov, Guoguo Chen, Daniel Povey, and Sanjeev Khudanpur · 2015
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Wavenet: A generative model for raw audio
Aaron van den Oord, Sander Dieleman, Heiga Zen, Karen Simonyan, Oriol Vinyals, Alex Graves, Nal Kalchbrenner, Andrew Senior, and Koray Kavukcuoglu · 2016
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Sergey Zagoruyko and Nikos Komodakis · 2016
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Identity mappings in deep residual networks
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Audio set: An ontology and human-labeled dataset for audio events
Jort F Gemmeke, Daniel PW Ellis, Dylan Freedman, Aren Jansen, Wade Lawrence, R Channing Moore, Manoj Plakal, and Marvin Ritter · 2017
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Practical black-box attacks against machine learning
Nicolas Papernot, Patrick McDaniel, Ian Goodfellow, Somesh Jha, Z Berkay Celik, and Ananthram Swami · 2017
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Feature visualization
Chris Olah, Alexander Mordvintsev, and Ludwig Schubert · 2017
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Raw waveform-based audio classification using sample-level cnn architectures
Jongpil Lee, Taejun Kim, Jiyoung Park, and Juhan Nam · 2017
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Prada: protecting against dnn model stealing attacks
Mika Juuti, Sebastian Szyller, Samuel Marchal, and N Asokan · 2019
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Targeted adversarial examples for black box audio systems, 2019
Rohan Taori, Amog Kamsetty, Brenton Chu, and Nikita Vemuri · 2019
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Sirenattack: Generating adversarial audio for end-to-end acoustic systems, 2019
Tianyu Du, Shouling Ji, Jinfeng Li, Qinchen Gu, Ting Wang, and Raheem Beyah · 2019
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Adversarial audio synthesis, 2019
Chris Donahue, Julian McAuley, and Miller Puckette · 2019
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Deep learning for audio signal processing
Hendrik Purwins, Bo Li, Tuomas Virtanen, Jan Schlüter, Shuo-Yiin Chang, and Tara Sainath · 2019
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Randomly weighted cnns for (music) audio classification
Jordi Pons and Xavier Serra · 2019
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Hongyi Zhang, Moustapha Cisse, Yann N Dauphin, and David Lopez-Paz · 2017
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Understanding black-box predictions via influence functions
Pang Wei Koh and Percy Liang · 2017
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Have you stolen my model? evasion attacks against deep neural network watermarking techniques, 2018
Dorjan Hitaj and Luigi V. Mancini · 2018
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Audio adversarial examples: Targeted attacks on speech-to-text, 2018
Nicholas Carlini and David Wagner · 2018
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Robust audio adversarial example for a physical attack
Hiromu Yakura and Jun Sakuma · 2018
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X-vectors: Robust dnn embeddings for speaker recognition
D. Snyder, D. Garcia-Romero, G. Sell, D. Povey, and S. Khudanpur · 2018
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Building a Speaker Identification System from Scratch with Deep Learning, October 2018
Oscar Knagg · 2018
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An end-to-end audio classification system based on raw waveforms and mix-training strategy
Jiaxu Chen, Jing Hao, Kai Chen, Di Xie, Shicai Yang, and Shiliang Pu · 2019
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Speaker recognition from raw waveform with sincnet, 2019
Mirco Ravanelli and Yoshua Bengio · 2019
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Thieves on sesame street! model extraction of bert-based apis
Kalpesh Krishna, Gaurav Singh Tomar, Ankur P Parikh, Nicolas Papernot, and Mohit Iyyer · 2019
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High fidelity speech synthesis with adversarial networks
Mikołaj Bińkowski, Jeff Donahue, Sander Dieleman, Aidan Clark, Erich Elsen, Norman Casagrande, Luis C Cobo, and Karen Simonyan · 2019
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Label-efficient audio classification through multitask learning and self-supervision
Tyler Lee, Ting Gong, Suchismita Padhy, Andrew Rouditchenko, and Anthony Ndirango · 2019
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Jean-Baptiste Truong, Pratyush Maini, Robert Walls, and Nicolas Papernot · 2020
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Voxceleb: Large-scale speaker verification in the wild
Arsha Nagrani, Joon Son Chung, Weidi Xie, and Andrew Zisserman · 2020
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Linguistic data consortium, 2021
LDC · 2021
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Deepdream, tensorflow tutorials, 2021
TensorFlow Tutorials · 2021
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