ISCA Archive S4SG 2022
ISCA Archive S4SG 2022

Highly Intelligible Speech Synthesis for Spinal Muscular Atrophy Patients Based on Model Adaptation

Takuma Yoshimoto, Ryoichi Takashima, Chiho Sasaki, Tetsuya Takiguchi

Recently, speech signal processing technology has been used to assist people with disabilities, and the demand for such technology is increasing. In this study, we focus on spinal muscular atrophy (SMA) patients. SMA is a neuromuscular disease. Those with this disease have speech that is unclear compared to that of normal subjects which results from the use of a ventilator after a tracheotomy and from the atrophy of muscles that move the mouth, etc. Therefore, it is difficult to understand what they are saying, making communication difficult. In this paper, we analyze the speech of people with SMA and propose a text-to-speech (TTS) system to aid in communication. The proposed system uses an approach that adapts a TTS model pre-trained using normal speech to speech of a person with SMA. This system can synthesize speech having both of intelligibility derived from normal speech and individuality derived from the speech of the target subject with SMA.


doi: 10.21437/S4SG.2022-8

Cite as: Yoshimoto, T., Takashima, R., Sasaki, C., Takiguchi, T. (2022) Highly Intelligible Speech Synthesis for Spinal Muscular Atrophy Patients Based on Model Adaptation. Proc. 1st Workshop on Speech for Social Good (S4SG), 36-40, doi: 10.21437/S4SG.2022-8

@inproceedings{yoshimoto22_s4sg,
  author={Takuma Yoshimoto and Ryoichi Takashima and Chiho Sasaki and Tetsuya Takiguchi},
  title={{Highly Intelligible Speech Synthesis for Spinal Muscular Atrophy Patients Based on Model Adaptation}},
  year=2022,
  booktitle={Proc. 1st Workshop on Speech for Social Good (S4SG)},
  pages={36--40},
  doi={10.21437/S4SG.2022-8}
}