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Adversarial attacks on audio source separation

Adversarial attacks on audio source separation

7 October 2020
Naoya Takahashi
S. Inoue
Yuki Mitsufuji
    AAML
ArXivPDFHTML

Papers citing "Adversarial attacks on audio source separation"

6 / 6 papers shown
Title
Music Source Separation in the Waveform Domain
Music Source Separation in the Waveform Domain
Alexandre Défossez
Nicolas Usunier
Léon Bottou
Francis R. Bach
90
269
0
27 Nov 2019
Imperceptible, Robust, and Targeted Adversarial Examples for Automatic
  Speech Recognition
Imperceptible, Robust, and Targeted Adversarial Examples for Automatic Speech Recognition
Yao Qin
Nicholas Carlini
Ian Goodfellow
G. Cottrell
Colin Raffel
AAML
42
379
0
22 Mar 2019
Conv-TasNet: Surpassing Ideal Time-Frequency Magnitude Masking for
  Speech Separation
Conv-TasNet: Surpassing Ideal Time-Frequency Magnitude Masking for Speech Separation
Yi Luo
N. Mesgarani
116
1,772
0
20 Sep 2018
Adversarial Attacks Against Automatic Speech Recognition Systems via
  Psychoacoustic Hiding
Adversarial Attacks Against Automatic Speech Recognition Systems via Psychoacoustic Hiding
Lea Schonherr
Katharina Kohls
Steffen Zeiler
Thorsten Holz
D. Kolossa
AAML
42
288
0
16 Aug 2018
MMDenseLSTM: An efficient combination of convolutional and recurrent
  neural networks for audio source separation
MMDenseLSTM: An efficient combination of convolutional and recurrent neural networks for audio source separation
Naoya Takahashi
Nabarun Goswami
Yuki Mitsufuji
55
143
0
07 May 2018
Intriguing properties of neural networks
Intriguing properties of neural networks
Christian Szegedy
Wojciech Zaremba
Ilya Sutskever
Joan Bruna
D. Erhan
Ian Goodfellow
Rob Fergus
AAML
101
14,831
1
21 Dec 2013
1