'Voice Conversion' paper candidate 2501.10256

[github-actions]

Please check whether this paper is about 'Voice Conversion' or not.

article info.

• title: Unsupervised Rhythm and Voice Conversion of Dysarthric to Healthy Speech for ASR

• summary: Automatic speech recognition (ASR) systems are well known to perform poorly
  on dysarthric speech. Previous works have addressed this by speaking rate
  modification to reduce the mismatch with typical speech. Unfortunately, these
  approaches rely on transcribed speech data to estimate speaking rates and
  phoneme durations, which might not be available for unseen speakers. Therefore,
  we combine unsupervised rhythm and voice conversion methods based on
  self-supervised speech representations to map dysarthric to typical speech. We
  evaluate the outputs with a large ASR model pre-trained on healthy speech
  without further fine-tuning and find that the proposed rhythm conversion
  especially improves performance for speakers of the Torgo corpus with more
  severe cases of dysarthria. Code and audio samples are available at
  https://idiap.github.io/RnV .

• id: http://arxiv.org/abs/2501.10256v1

judge

Write [vclab::confirmed] or [vclab::excluded] in comment.