Xinghui-Wu/KENKU
KENKU: Towards Efficient and Stealthy Black-box Adversarial Attacks against ASR Systems
This project helps security researchers and penetration testers evaluate the robustness of Automatic Speech Recognition (ASR) systems. It takes audio clips (like songs) and target command texts as input to generate altered audio files. These altered files, when played, sound normal to humans but trick ASR systems into transcribing a hidden command. The output is audio that sounds like music but makes an ASR system transcribe a secret message, revealing vulnerabilities.
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Use this if you are a security researcher or red team member looking to test the resilience of commercial ASR systems against 'hidden voice command' or 'integrated command' attacks.
Not ideal if you are looking for a general-purpose ASR system or a tool to improve speech recognition accuracy.
Stars
20
Forks
1
Language
Python
License
MIT
Category
Last pushed
Oct 03, 2023
Commits (30d)
0
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