'Voice Conversion' paper candidate 2410.15500

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article info.

• title: Anonymising Elderly and Pathological Speech: Voice Conversion Using DDSP and Query-by-Example

• summary: Speech anonymisation aims to protect speaker identity by changing personal
  identifiers in speech while retaining linguistic content. Current methods fail
  to retain prosody and unique speech patterns found in elderly and pathological
  speech domains, which is essential for remote health monitoring. To address
  this gap, we propose a voice conversion-based method (DDSP-QbE) using
  differentiable digital signal processing and query-by-example. The proposed
  method, trained with novel losses, aids in disentangling linguistic, prosodic,
  and domain representations, enabling the model to adapt to uncommon speech
  patterns. Objective and subjective evaluations show that DDSP-QbE significantly
  outperforms the voice conversion state-of-the-art concerning intelligibility,
  prosody, and domain preservation across diverse datasets, pathologies, and
  speakers while maintaining quality and speaker anonymity. Experts validate
  domain preservation by analysing twelve clinically pertinent domain attributes.

• id: http://arxiv.org/abs/2410.15500v1

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