English

ClaritySpeech: Dementia Obfuscation in Speech

Computation and Language 2025-07-15 v1 Cryptography and Security Machine Learning Sound Audio and Speech Processing

Abstract

Dementia, a neurodegenerative disease, alters speech patterns, creating communication barriers and raising privacy concerns. Current speech technologies, such as automatic speech transcription (ASR), struggle with dementia and atypical speech, further challenging accessibility. This paper presents a novel dementia obfuscation in speech framework, ClaritySpeech, integrating ASR, text obfuscation, and zero-shot text-to-speech (TTS) to correct dementia-affected speech while preserving speaker identity in low-data environments without fine-tuning. Results show a 16% and 10% drop in mean F1 score across various adversarial settings and modalities (audio, text, fusion) for ADReSS and ADReSSo, respectively, maintaining 50% speaker similarity. We also find that our system improves WER (from 0.73 to 0.08 for ADReSS and 0.15 for ADReSSo) and speech quality from 1.65 to ~2.15, enhancing privacy and accessibility.

Keywords

Cite

@article{arxiv.2507.09282,
  title  = {ClaritySpeech: Dementia Obfuscation in Speech},
  author = {Dominika Woszczyk and Ranya Aloufi and Soteris Demetriou},
  journal= {arXiv preprint arXiv:2507.09282},
  year   = {2025}
}

Comments

Accepted at Interspeech 2025

R2 v1 2026-07-01T03:57:57.274Z