Reprogramming Self-supervised Learning-based Speech Representations for Speaker Anonymization

Author:

Chen Xiaojiao1ORCID,Li Sheng2ORCID,Li Jiyi3ORCID,Huang Hao1ORCID,Cao Yang4ORCID,He Liang5ORCID

Affiliation:

1. Xinjiang University, CN

2. National Institute of Information and Communications Technology (NICT), JP

3. University of Yamanashi, JP

4. Hokkaido University, JP

5. Tsinghua University, CN

Funder

JSPS KAKENHI Grant No.

Publisher

ACM

Reference27 articles.

1. Alexei Baevski , Yuhao Zhou , Abdelrahman Mohamed , and Michael Auli . 2020. wav2vec 2.0: A framework for self-supervised learning of speech representations. Advances in neural information processing systems 33 ( 2020 ), 12449–12460. Alexei Baevski, Yuhao Zhou, Abdelrahman Mohamed, and Michael Auli. 2020. wav2vec 2.0: A framework for self-supervised learning of speech representations. Advances in neural information processing systems 33 (2020), 12449–12460.

2. WavLM: Large-Scale Self-Supervised Pre-Training for Full Stack Speech Processing

3. Gamaleldin  F Elsayed , Ian Goodfellow , and Jascha Sohl-Dickstein . 2019 . Adversarial Reprogramming of Neural Networks. In International Conference on Learning Representations. Gamaleldin F Elsayed, Ian Goodfellow, and Jascha Sohl-Dickstein. 2019. Adversarial Reprogramming of Neural Networks. In International Conference on Learning Representations.

4. F. Fuming and 2019. Speaker anonymization using x-vector and neural waveform models. arXiv preprint arXiv:1905.13561 ( 2019 ). F. Fuming and et al.2019. Speaker anonymization using x-vector and neural waveform models. arXiv preprint arXiv:1905.13561 (2019).

5. Y. Ganin E. Ustinova H. Ajakan P. Germain H. Larochelle F. Laviolette M. Marchand and V. Lempitsky. 2016. Domain-adversarial training of neural networks. The journal of machine learning research 17 1 (2016) 2096–2030. Y. Ganin E. Ustinova H. Ajakan P. Germain H. Larochelle F. Laviolette M. Marchand and V. Lempitsky. 2016. Domain-adversarial training of neural networks. The journal of machine learning research 17 1 (2016) 2096–2030.

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