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Targeted Adversarial Examples for Black Box Audio Systems

Sample code to let you create your own adversarial examples! Paper linked here.

Installation

Note: linux platform required as this code uses an old version of tensorflow (1.8).

Dependencies: cuda 9.0, python 3.6, requirements.txt.

For example, if using anaconda (and on cuda9.0), create an environment and install the requirements:

conda create --name adversarialaudio python=3.6
conda activate adversarialaudio
pip install -r requirements.txt

Then clone the DeepSpeech repository and download the model at the appropriate version:

git clone -b 'v0.1.1' --single-branch --depth 1 https://github.com/mozilla/DeepSpeech.git
wget https://github.com/mozilla/DeepSpeech/releases/download/v0.1.1/deepspeech-0.1.1-models.tar.gz
tar -xzf deepspeech-0.1.1-models.tar.gz && rm deepspeech-0.1.1-models.tar.gz

Finally, create the checkpoint used for the attack:

python make_checkpoint.py

DeepSpeech may throw a warning saying "decoder library file does not exist" but that can be ignored.

Running Attacks

Now create and run an attack, for example:

python run_audio_attack.py sample_input.wav "hello world"

Of course, sample_input.wav may be changed to any input audio file and "hello world" may be changed to any target transcription.

You can also listen to pre-created audio samples in the samples directory. Each original/adversarial pair is denoted by a leading number, with model transcriptions as the title.

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