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Whispering Under the Eaves: Protecting User Privacy Against Commercial and LLM-powered Automatic Speech Recognition Systems

Name: Whispering Under the Eaves: Protecting User Privacy Against Commercial and LLM-powered Automatic Speech Recognition Systems
Creator: Jin, Weifei

descriptionPublicationkeyboard_double_arrow_right Article 21 Jan 2025Publisher:Zenodo

Authors: Jin, Weifei;

doi: 10.5281/zenodo.15107224 , 10.5281/zenodo.14711220 , 10.5281/zenodo.14711219

Whispering Under the Eaves: Protecting User Privacy Against Commercial and LLM-powered Automatic Speech Recognition Systems

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Abstract

Here are the materials related to AudioShield, including: source_code.zip: The source code of AudioShield. datasets.zip: The training and testing datasets, processed in pickle format and ready for use. The 500 samples from Librispeech are used for training, and 2000 samples from VCTK are used for testing. pretrained_models.zip: The pre-trained models required for training and testing, including the locally trained target ASR model, DeepSpeech, and the Autoencoder model VITS used by AudioShield. Please unzip the files in datasets.zip into the source_code/datasets folder, and unzip the files in pretrained_models.zip into the source_code/pretrained folder. For detailed installation and usage instructions, please refer to the README file in the source_code folder.

Related Organizations

Beijing University of Posts and Telecommunications
China (People's Republic of)

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