Silent-Hidden-Voice Attack on Speech Recognition System

In this paper, we propose a method for creating a hidden voice that is perceived as silence by a human. The proposed method creates a silent hidden voice that is mistakenly classified as a target phrase by the target model; it does this by configuring the loss function so that the probability of cla...

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Bibliographic Details
Main Authors: Hyun Kwon, Dooseo Park, Ohyun Jo
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/10443869/
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Summary:In this paper, we propose a method for creating a hidden voice that is perceived as silence by a human. The proposed method creates a silent hidden voice that is mistakenly classified as a target phrase by the target model; it does this by configuring the loss function so that the probability of classification into the target phrase by the target model is highest. In an experimental evaluation using the Mozilla Common Voice dataset as the test data source and TensorFlow as the machine learning library, the proposed method created a silent hidden voice that had a 100% attack success rate for a target phrase on a target model while minimizing the average distortion to 187.81.
ISSN:2169-3536