Privacy versus Emotion Preservation Trade-offs in Emotion-Preserving Speaker Anonymization

• URL: http://arxiv.org/abs/2409.03655v1
• Date: Thu, 5 Sep 2024 16:10:31 GMT
• Title: Privacy versus Emotion Preservation Trade-offs in Emotion-Preserving Speaker Anonymization
• Authors: Zexin Cai, Henry Li Xinyuan, Ashi Garg, Leibny Paola García-Perera, Kevin Duh, Sanjeev Khudanpur, Nicholas Andrews, Matthew Wiesner,
• Abstract summary: differential privacy field has explored ways to anonymize speech while preserving its utility. We develop various speaker anonymization pipelines and find that approaches either excel at anonymization or preserving emotion state, but not both simultaneously.
• Score: 31.94758615908198
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Advances in speech technology now allow unprecedented access to personally identifiable information through speech. To protect such information, the differential privacy field has explored ways to anonymize speech while preserving its utility, including linguistic and paralinguistic aspects. However, anonymizing speech while maintaining emotional state remains challenging. We explore this problem in the context of the VoicePrivacy 2024 challenge. Specifically, we developed various speaker anonymization pipelines and find that approaches either excel at anonymization or preserving emotion state, but not both simultaneously. Achieving both would require an in-domain emotion recognizer. Additionally, we found that it is feasible to train a semi-effective speaker verification system using only emotion representations, demonstrating the challenge of separating these two modalities.

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