HLTCOE JHU Submission to the Voice Privacy Challenge 2024

Henry Li Xinyuan, Zexin Cai, Ashi Garg, Kevin Duh, Leibny Paola García-Perera +3 more
9/13/2024
eess.AScs.LG

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Abstract

We present a number of systems for the Voice Privacy Challenge, including voice conversion based systems such as the kNN-VC method and the WavLM voice Conversion method, and text-to-speech (TTS) based systems including Whisper-VITS. We found that while voice conversion systems better preserve emotional content, they struggle to conceal speaker identity in semi-white-box attack scenarios; conversely, TTS methods perform better at anonymization and worse at emotion preservation. Finally, we propose a random admixture system which seeks to balance out the strengths and weaknesses of the two category of systems, achieving a strong EER of over 40% while maintaining UAR at a respectable 47%.

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Cite this paper

@article{xinyuan2024hltcoe,
  title  = {HLTCOE JHU Submission to the Voice Privacy Challenge 2024},
  author = {Henry Li Xinyuan and Zexin Cai and Ashi Garg and Kevin Duh and Leibny Paola García-Perera and Sanjeev Khudanpur and Nicholas Andrews and Matthew Wiesner},
  year   = {2024},
  eprint = {2409.08913},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2409.08913v2}
}

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