Lightweight and irreversible speech pseudonymization based on data-driven optimization of cascaded voice modification modules

Author:

Kai Hiroto,Takamichi Shinnosuke,Shiota Sayaka,Kiya Hitoshi

Funder

Japan Society for the Promotion of Science

Secom Science and Technology Foundation

Publisher

Elsevier BV

Subject

Human-Computer Interaction,Theoretical Computer Science,Software

Reference29 articles.

1. Akiba, T., Sano, S., Yanase, T., Ohta, T., Koyama, M., 2019. Optuna: A next-generation hyperparameter optimization framework. In: Proc. ACM SIGKDD. Alaska, U.S.A. 2019. pp. 2623–2631.

2. Bahmaninezhad, F., Zhang, C., Hansen, J., 2018. Convolutional neural network based speaker de-identification. In: Proc. Odyssey. Les Sables d’Olonne, France, pp. 255–260.

3. Speaker Information Modification in the VoicePrivacy 2020 Toolchain;Champion,2020

4. Adjustable deterministic pseudonymisation of speech: Idiap-NKI’s submission to VoicePrivacy 2020 challenge;Dubagunta,2020

5. Speaker de-identification system using autoencoders and adversarial training;Espinoza-Cuadros,2020

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Anonymizing Speech with Generative Adversarial Networks to Preserve Speaker Privacy;2022 IEEE Spoken Language Technology Workshop (SLT);2023-01-09

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